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2024-03-07 19:40:17

LKB1_百度百科

_百度百科网页新闻贴吧知道网盘图片视频地图文库资讯采购百科百度首页登录注册进入词条全站搜索帮助首页秒懂百科特色百科知识专题加入百科百科团队权威合作下载百科APP个人中心收藏查看我的收藏0有用+10LKB1播报讨论上传视频抑癌基因本词条缺少概述图，补充相关内容使词条更完整，还能快速升级，赶紧来编辑吧！人LKB1(Liver kinase B1)基因或称STK 11（Serine-Threonine Kinase 11，STK 11），定位于人染色体19p 13 .3的位置。含10个外显子，编码蛋白LKB1由433个氨基酸组成, 分子量约50 kda，包括激酶区域(44~309 ) ，N 端调节域和C 端调节域。N 端调节域含一个核定位序列, 使LKB1定位于细胞核中。LKB1 在人体多种组织中广泛表达。以幼肝，睾丸，小肠和骨骼肌最多。外文名LKB1别名Liver kinase B1分子量约50 kda氨基酸433个目录1简介2功能简介播报编辑LKB1基因的胚系失活突变可导致癌症易感病皮杰氏综合征(Peutz-Jeghers syndrome, PJ S) , 该病患者多发错构瘤息肉且患癌症风险增加。LKB1基因的体细胞突变广泛地存在于众多类型的恶性肿瘤中, 如肺癌。结肠癌和乳腺癌等, 因此,LKB1被普遍认为是抑癌基因。LKB1基因的编码产物LKB1蛋白是一种丝氨酸/苏氨酸激酶, 调节多种细胞生理病理过程。功能播报编辑重要的蛋白激酶LKB1的直接底物包括AMPK(AMP-activated protein kinase)和十二种AMPK激酶。LKB1通过促进AMPK α亚基上Thr172位点的磷酸化，增强AMPK的磷酸化水平，从而使AMPK激活。细胞生长的负因子LKB1可以通过激活AMPK来抑制真核细胞生长正调节因子mTORC1(mammalian target of rapamycin complex 1)的活性，而mTORC1可促进细胞生长和细胞周期的进程。在许多肿瘤细胞中，mTORC1的活性都被异常激活。抑制合成代谢LKB1激活AMPK后，AMPK可快速失活脂酸和胆固醇合成限速酶—乙酰辅酶A羧化酶（acetyl-CoA carboxylase，ACC）和HMG-辅酶A还原酶（HMGCR）从而抑制脂类合成，降低能量消耗。同时快速调节糖酵解关键酶6-磷酸果糖激酶活性而促进糖酵解产生能量。ACC等酶类是一些肿瘤细胞生存所必须的，化学抑制其活性可抑制癌症和前列腺癌移植瘤的生长。新手上路成长任务编辑入门编辑规则本人编辑我有疑问内容质疑在线客服官方贴吧意见反馈投诉建议举报不良信息未通过词条申诉投诉侵权信息封禁查询与解封©2024 Baidu 使用百度前必读 | 百科协议 | 隐私政策 | 百度百科合作平台 | 京ICP证030173号京公网安备110000020000

季红斌研究组发表Cancer Cell封面文章：LKB1失活引起的氧化还原态失衡调控非小细胞肺癌可塑性和药物反应--中国科学院分子细胞科学卓越创新中心

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季红斌研究组发表Cancer Cell封面文章：LKB1失活引起的氧化还原态失衡调控非小细胞肺癌可塑性和药物反应

来源：

时间：2015-07-27

2015年5月1日，国际学术期刊Cancer Cell 在线发表了中国科学院上海生命科学研究院生物化学与细胞生物学研究所季红斌研究组的最新研究成果“LKB1 Inactivation Elicits a Redox Imbalance to Modulate Non-Small Cell Lung Cancer Plasticity and Therapeutic Response”。该研究深入揭示了LKB1失活调控非小细胞肺癌可塑性及药物响应的重要功能和相关机制，为认识人类肺癌的发病机理提供了新的视角和思路，对肺癌的诊断和治疗具有重要的临床指导意义。该研究将作为Cancer Cell 五月期刊封面文章刊出。

肺癌的发病率和致死率历年来一直高居恶性肿瘤榜首。非小细胞肺癌是肺癌的主要类型，具有显著的遗传多样性和病理组织异质性。临床上，20%以上的非小细胞肺癌患者携带LKB1的失活型突变，对这类患者目前尚无有效的治疗策略。季红斌研究组长期致力于研究LKB1在肺癌发病过程中的功能和机制。前期工作发现在Kras/Lkb1肺癌小鼠模型中敲除LKB1不仅促进肺癌发生和肿瘤进程，还特异地导致了肿瘤异质性，即肺腺癌、鳞癌和腺鳞癌的出现 (Ji H et al, Nature, 2007)。近年来，他们进一步证实这种肺癌异质性源于LKB1缺失引起的肿瘤可塑性，即肺腺癌经由混合型腺鳞癌转分化为肺鳞癌 (Han X et al, Nature Communications, 2014; Gao Y et al, Nature Communications, 2014)。值得注意的是，LKB1的功能具有“双面性”：作为经典的抑癌基因，LKB1的失活可促进细胞增殖和加速肿瘤进程；作为细胞的能量感应和维持应激条件下代谢稳态的关键分子，LKB1的失活使得细胞缺乏对代谢应激的适应能力。因此，缺失LKB1的肺癌细胞如何在体内应对肿瘤进程和代谢应激这一矛盾并协调其可塑性仍然是一个尚未解决的科学问题。

在季红斌研究员的指导下，博士后李福明、助理研究员韩向琨和博士生李飞结合多种实验手段发现Kras/Lkb1小鼠肺腺癌中活性氧簇(Reactive Oxygen Species, ROS)的水平明显高于肺鳞癌; 降低肺腺癌中的ROS水平可抑制其向肺鳞癌的转分化。进一步发现，肺腺癌中ROS的异常积累源于戊糖磷酸途径(pentose phosphate pathway, PPP)下调和脂肪酸氧化(Fatty Acid Oxidation, FAO)通路失活引起的氧化还原态失衡。临床样本的分析证实，LKB1缺失的部分肺腺癌样本呈现出鳞癌特征基因的表达，而LKB1缺失的部分肺鳞癌样本呈现出腺癌特征基因的表达；此外，PPP、FAO通路和氧化还原的标志性基因在这些样本中呈现和小鼠肿瘤一致的差异表达特征。利用Kras/Lkb1模型进行临床前实验发现，缺失LKB1的肺腺癌和肺鳞癌对ROS诱导剂Piperlongumine和代谢药物Phenformin具有不同的敏感性；虽然这两种药物对肺腺癌有一定的疗效，却会促使一部分肺腺癌转分化为肺鳞癌从而导致肿瘤耐药性的产生。

结合研究组之前的研究结果(Gao et al, PNAS, 2010)，他们提出LKB1在非小细胞肺癌进展过程中的阶段特异性功能，即早期作为抑癌基因，晚期作为氧化还原／代谢稳态的调控因子。LKB1失活引起的氧化还原态失衡使得肺腺癌异常积累ROS，而后者促使肺腺癌转分化为鳞癌，并获得更强的代谢应激适应能力。更重要的是，这种转分化影响肿瘤细胞对靶向代谢药物的响应和疗效，这提示临床上LKB1失活的肺腺癌有可能通过转分化为肺鳞癌来逃脱某些靶向肿瘤代谢的药物治疗。为了更好地实现临床精准医疗，发生耐药的肺癌患者可能需要进一步的活检来确证其病理类型是否发生改变，从而对症下药。

该项工作和复旦大学附属肿瘤医院陈海泉教授课题组合作完成，得到了营养所翟琦巍研究员、美国哈佛医学院Kwok-Kin Wong教授等的大力支持和帮助。该研究得到中国科学院、国家科技部、国家自然科学基金委、上海市科委以及上海生科院的经费支持。

图：LKB1失活调控非小细胞肺癌进展的阶段特异性功能模型

当期Cancer Cell 封面

In Chinese fairy tale, the Monkey King were captured and burned with Samadhi fire in the Stove of Senior moral (Taishang laojun) and 49 days later, the Monkey King didn’t die as expected; instead, it gains even stronger magic power with piercing eyes. Similarly, LKB1-deficient lung adenocarcinoma harbors strong plasticity and even under highly deregulated oxidative stress illustrated as Samadhi fire, these lung adenocarcinomas go through systematic reprogramming and gains super power to become drug resistant through the transition to squamous cell carcinomas.

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LKB1-AMPK-mTOR信号传导通路在肿瘤中的研究进展 - PMC

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Zhongguo Fei Ai Za Zhi

v.14(8); 2011 Aug 20

PMC5999621

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Zhongguo Fei Ai Za Zhi. 2011 Aug 20; 14(8): 685–688. Chinese. doi: 10.3779/j.issn.1009-3419.2011.08.09PMCID: PMC5999621PMID: 21859551LKB1-AMPK-mTOR信号传导通路在肿瘤中的研究进展Advances of LKB1-AMPK-mTOR Signaling Pathway in Tumor张霞1张霞

300052 天津，天津医科大学总医院呼吸科,

Department of Respiratory Medicine, Tianjin Medical University General Hospital, Tianjin 300052, China

Find articles by 张霞Reviewed by 孙琳琳2孙琳琳

天津医科大学总医院，天津市肺癌研究所，天津市肺癌转移与肿瘤微环境实验室,

Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin 300052, China

Find articles by 孙琳琳Guest Editor (s): 钟殿胜1,2,*Author information Article notes Copyright and License information PMC Disclaimer钟殿胜: moc.liamtoh@hsdgnohz 钟殿胜, Diansheng ZHONG, E-mail: moc.liamtoh@hsdgnohzReceived 2011 Jun 28; Revised 2011 Jul 6Copyright 版权所有©《中国肺癌杂志》编辑部2011Copyright ©2011 Chinese Journal of Lung Cancer. All rights reserved.This is an open access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 3.0) License. See: https://creativecommons.org/licenses/by/3.0/肿瘤可以认为是一种基因疾病，其中癌基因的激活和抑癌基因的失活是肿瘤发生、发展过程中最为关键的环节之一[1]。近年来，一个新的抑癌基因LKB1，又名STK11(serine threonine protein kinase 11)，在肿瘤中的作用引起了越来越多的关注。哺乳动物雷帕霉素靶蛋白(mammalian target of rapamycin, mTOR)信号通路是目前肿瘤信号传导通路研究的热点之一。研究[2]显示LKB1通过磷酸化磷酸腺苷激活的蛋白激酶(AMP-activated protein kinase, AMPK)，从而激活AMPK，实现对mTOR活性的负向调控。本文就LKB1-AMPK-mTOR信号通路及其在肿瘤中的研究进展进行简要的综述。1. LKB1的结构与功能LKB1基因位于人的第19号染色体短臂13.3区，包含9个编码的外显子和1个非编码外显子，其编码的LKB1蛋白由433个氨基酸组成，属于丝氨酸/苏氨酸蛋白激酶，第44-309位氨基酸为激酶催化区，N端第38-43位氨基酸残基是核定位信号序列(nuclear localization signal, NLS)，该序列的缺失将导致LKB1遍布整个细胞，但不影响其抑制细胞生长的功能。LKB1蛋白主要定位于细胞核，细胞浆中只有少量表达，但其功能主要与细胞浆内的部分有关[3]。LKB1与STRAD(STE20 related adaptor protein)和MO25(mouse protein 25)蛋白形成复合体，可极大地提高其激酶活性。STRAD蛋白缺少催化蛋白质磷酸化所必须的关键残基(即Vib和VII两个模体)，是一个假激酶，当STRAD与LKB1形成复合体后，可促进后者从细胞核内移位到细胞浆内[4]；MO25蛋白与STRAD羧基端结合，增加了LKB1-STRAD复合物在细胞浆中的空间定位和构象，使LKB1的活性提高了近10倍[5]。Rowan等[6]研究表明，人体中几乎所有的组织均有LKB1 mRNA的表达，其中胎儿组织中的表达高于成人，成人以上皮、睾丸生精小管和肝脏表达最强。LKB1基因的胚系突变(germline mutation)是黑斑息肉综合征(Peutz-Jeghers syndrome, PJS)的主要致病原因[7]。PJS是一种以胃肠道多发性错构瘤息肉样改变和黏膜色素沉着为特征的常染色体显性遗传疾病，该类患者的肿瘤发生率是普通人群的10倍-18倍[8]，以消化道肿瘤最常见，还可伴发其它部位，如乳腺、子宫、卵巢、睾丸和胰腺等的肿瘤[9]。66%-94%的PJS患者可以检测到LKB1基因突变，突变类型以点突变、小片段插入或缺失为主，也可有整个外显子或基因的缺失[10, 11]。LKB1基因的突变使LKB1蛋白丧失了激酶活性，从而失去对细胞生长的控制，导致肿瘤的发生[12]。研究显示，绝大多数散发性肿瘤中，LKB1体细胞突变是罕见的[13]，但在非小细胞肺癌(non-small cell lung cancer, NSCLC)中，LKB1 的突变率可高达15%-35%[14]。LKB1可参与细胞内多种生物活动，在控制和调节细胞能量代谢、细胞增殖、细胞周期、细胞凋亡和细胞极性中发挥着重要作用[15]。将外源性LKB1基因导入无LKB表达的HeLa(宫颈癌细胞)和G361(恶性黑色素瘤细胞)中，可导致p21蛋白表达的增加，使细胞周期阻滞于G1期，抑制了细胞的增生[16]。Ji等[17]发现，LKB1在肺癌的发生起始、分化、转移中起着至关重要的作用。关于LKB1信号传导途径，目前了解的并不多。Alessi等[18]报道，LKB1可以磷酸化AMPKa亚单位活化环上172位点的苏氨酸，从而激活AMPK。2. LKB1是AMPK的上游激酶AMPK是一个异源三聚体蛋白，由一个具有催化活性的α亚单位及两个具有调节功能的β和γ亚单位组成，各个亚单位又可进一步分为α1、α2和β1、β2，γ1、γ2、γ3，不同的亚单位自由排列组合可以形成多种不同的AMPK三聚体[19]。α亚单位具有催化活性，有2个功能区，N端含有催化区域，是活性的核心部位，C末端含有与β和γ亚单位结合的区域，负责活性的调节；β亚基有2个相同的保守区域，分别为KIS和ASC区域。研究[20]表明，哺乳动物的ASC区域参与α和γ亚基的结合，KIS区域可能是一个糖原结合区，主要参与糖原的结合，对异源三聚体的定位非常重要；γ亚基含有4个串行重复的区域，命名为CBS(cystathionine beta synthase)区域，CBS在C端有2个这样的重复区域，每个区域约有60个氨基酸残基，它们借疏水作用力结合在一起，是AMP的结合位点。AMPK是哺乳动物细胞中高度保守的蛋白质，是细胞的“代谢和能量感受器”。它对细胞内AMP/ATP比值变化相当敏感，在各种应激(缺氧、缺血、营养物质缺乏、运动等)下，AMP/ATP比值增加，AMPK活化，通过下调合成代谢过程(如蛋白质、脂肪酸和胆固醇的合成)减低ATP的消耗，同时促进催化氧化过程(如脂肪酸氧化、糖酵解等)以生成更多的ATP，缓解应激，维持机体的正常代谢[21]。研究[22, 23]指出，应用AMPK激动剂，AICAR(5-氨基-4咪唑甲酰胺核苷酸)和苯乙双胍，处理HT1080(纤维肉瘤细胞）和LKB1+/+MEF（小鼠胚胎成纤维细胞）细胞，可以使AMPKa亚单位活化环上172位点的苏氨酸磷酸化（p-AMPK-a-Thr172），AMPK活化，而HeLa（不表达LKB1）和LKB1-/-MEF则无AMPK的活化；如果将野生型的LKB1基因导入HeLa和LKB1-/-MEF细胞后，再给于AICAR等处理，可以观察到AMPK的活化。Zhong等[24]应用AMPK激动剂，2-脱氧葡萄糖（2-deoxyglucose, 2-DG），处理LKB1野生型NSCLC细胞系H1299和H1792后，观察到p-AMPK-a-Thr172升高，而在LKB1基因突变细胞系A549、H460中，p-AMPK-a-Thr172无改变。上述研究提示LKB1是AMPK的上游激酶。此外，Karuman等[3]报道，在HT1080、IEC16(上皮细胞)和MEF等细胞中，LKB1可诱导细胞凋亡，并与P53蛋白功能有关。但张霞等[25]研究显示，P53突变或缺失并未影响到LKB1对AMPK的磷酸化作用，即LKB1-AMPK信号传导途径的调节与P53基因无关，所以LKB1与P53之间的信号传导联系还不是非常明确，有待进一步研究。AMPK除了在调节能量代谢方面起重要作用外，活化的AMPK还可以磷酸化结节性硬化复合物(tuberous sclerosis complex)TSC1-TSC2，TSC复合物可抑制小GTP酶Rheb(Rashomolog enriched in brain)，而后者是mTOR活化所必需的刺激蛋白。在缺氧、营养匮乏等应激下，LKB1通过激活AMPK，进而磷酸化TSC1-TSC2，抑制Rheb的活性，负向调控mTOR的功能[26]。3. LKB1-AMPK负向调控mTOR的功能mTOR蛋白是一种非典型的丝氨酸/苏氨酸蛋白激酶，是磷脂酰肌醇32激酶相关激酶(phosphatidylinositol 32 kinase related kinase, PIKK)蛋白家族之一。mTOR蛋白的FRB(FKBP12-rapamycin binding)激酶结构域是雷帕霉素(rapamycin)的结合位点，当雷帕霉素与FRB区域结合后，可以抑制mTOR的激酶活性。mTOR对生长因子、胰岛素、营养物质、氨基酸、葡萄糖等刺激产生应答，在调节细胞生长、增殖、调控细胞周期等多个方面扮演着重要角色。细胞受到生长因子等刺激后，磷脂酰肌醇3-羟基激酶(PI3K)活化，磷酸化其底物3, 4二磷酸磷脂酰肌醇(PIP2)转化成3, 4, 5三磷酸磷脂酰肌醇(PIP3)，进而通过磷脂酰肌醇依赖性激酶1、2(PDK1、PDK2)磷酸化Akt(蛋白激酶B)第308位点上的苏氨酸(Thr308)和第473位点上的丝氨酸(Ser473)，正向调节mTOR的功能[27]。活化的mTOR主要通过磷酸化蛋白翻译过程中的核糖体蛋白S6激酶(ribosomal protein S6 kinases, S6K)和真核细胞翻译启始因子4E结合蛋白1(the eIF4E-binding protein1, 4E-BP1)来控制细胞生长，二者是蛋白翻译的关键调节因子。S6K第389位苏氨酸可直接被mTOR磷酸化，磷酸化的S6K (p-S6K)可以促进延长因子-1a(elongation fator-1a, EF1a)、poly(A)结合蛋白等蛋白质翻译及表达[28]。S6K在多种人类肿瘤中呈高表达，S6K高表达的肿瘤预后较差[29]。eIF4E(eukaryotic translation initiation factor 4E)是真核细胞翻译启始复合体的亚单位之一，可与eIF4G结合，二者的结合受到4E-BPs的调节。低磷酸化的4E-BP1与eIF4E具有较高的亲和力，而处于高磷酸化状态的4E-BP1则可释放出eIF4E，使其与eIF4G结合，进而启动的5' cap mRNA的翻译。所以，当4E-BP1经mTOR作用发生磷酸化后，磷酸化的4E-BP1与elF4E发生分离，解除了翻译起始的抑制作用，从而增加了细胞周期蛋白D1、Rb蛋白、低氧诱导因子-1(hypoxia inducible factor-1, HIF-1)、血管内皮生长因子(vascular endothelial growth factor, VEGF)、CLIP-170等一组促进细胞生长关键蛋白的翻译，利于细胞的生长。目前已知，人的4E-BP1磷酸化位点有7个，分别是Thr37、Thr46、Ser65、Thr70、Ser83、Ser101和Ser112[30]。在生长因子的刺激下，mTOR首先磷酸化4E-BP1的Thr37和Thr46，进而磷酸化Thr70和Ser65。其中Thr70和Ser65的磷酸化对于eIF4E的释放最为重要，Thr70促进释放，而Ser65可以防止二者重新结合[31]，Zhou等[32]研究发现，mTOR、4E-BP1的磷酸化水平从正常乳腺上皮组织、不典型增生到恶性转化再到肿瘤浸润渐次增加，4E-BP1磷酸化水平越高，预后越差。所以mTOR信号通路的过度活化与肿瘤的发生、发展密切相关。研究[2]表明，在能量短缺时，LKB1通过激活AMPKTSC2，抑制mTOR，抑制S6K和4E-BP1的磷酸化。在LKB1-/-MEF中，LKB1基因功能丧失，mTOR信号高度活化，S6K和4E-BP1磷酸化水平增高；而在HeLa(无LKB1表达)细胞中重新导入野生型LKB1，恢复LKB1的功能，可以观察到S6K和4E-BP1磷酸化水平的下降。另有研究[33]证明，应用AMPK激动剂(AICAR)注射大鼠腓肠肌可导致mTOR Ser2448、S6K Thr389、4E-BP1 Thr37位点磷酸化水平显著下降，其结果抑制了mTOR活性和蛋白质合成，阻止新生小鼠心肌肥厚。Zhong等[24]应用AMPK抑制剂(Compound C)预处理NSCLC细胞系H1299，可以阻止AMPK激动剂(2-DG)引起的S6KThr389位点磷酸化水平减低。综上所述，LKB1通过AMPK实现对mTOR的负向调控。4. 结语和前景LKB1-AMPK-mTOR信号通路在调节细胞代谢、生长、增殖和凋亡中发挥着重要作用，LKB1的突变失活可导致mTOR信号通路异常活化，从而促进肿瘤的发生和发展。由于LKB1突变率在NSCLC中高达15%-35%，因此在肺癌中对该信号通路进行深入的探索是有意义的，可能为肺癌的靶向治疗提供新的思路。Funding Statement本研究受国家自然科学基金（No.30971307）和天津市应用基础及前沿技术研究基金（No.10JCYBJCI3700）资助This study was supported by grants from National Natural Science Foundation of China (to Diansheng ZHONG)(No.30971307) and Tianjin Natural Science Foundation (to Diansheng ZHONG)(No.10JCYBJC13700)References1. 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The LKB1–AMPK pathway: metabolism and growth control in tumour suppression | Nature Reviews Cancer

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nature

nature reviews cancer

review articles

article

Review Article

Published: August 2009

The LKB1–AMPK pathway: metabolism and growth control in tumour suppression

David B. Shackelford1 & Reuben J. Shaw1,2

Nature Reviews Cancer

volume 9, pages 563–575 (2009)Cite this article

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Key Points

The serine–threonine liver kinase B1 (LKB1) is inactivated in Peutz–Jeghers syndrome and a large percentage of sporadic non-small cell lung carcinomas and cervical carcinomas.

LKB1 acts a master upstream kinase, directly phosphorylating and activating AMP-activated protein kinase (AMPK) and a family of 12 related kinases that have crucial roles in cell growth, metabolism and polarity.

The LKB1–AMPK pathway serves as a metabolic checkpoint in the cell, arresting cell growth in conditions of low intracellular ATP levels, such as in low nutrient conditions.

One of the central mitogenic pathways that is suppressed by LKB1 and AMPK signalling is the mTOR complex 1 pathway, which is inhibited through AMPK phosphorylation of tuberous sclerosis complex 2 and regulatory associated protein of mTOR (raptor).

Overnutrition and hyperglycaemia can suppress LKB1–AMPK signalling, which might contribute to an increased cancer risk in patients who are obese or diabetic. Conversely, activation of LKB1–AMPK signalling might contribute to the suppression of cancer risk that is associated with exercise and caloric restriction. Will AMPK-activating drugs, including existing diabetes therapeutics, find clinical usefulness as anticancer agents?

AbstractIn the past decade, studies of the human tumour suppressor LKB1 have uncovered a novel signalling pathway that links cell metabolism to growth control and cell polarity. LKB1 encodes a serine–threonine kinase that directly phosphorylates and activates AMPK, a central metabolic sensor. AMPK regulates lipid, cholesterol and glucose metabolism in specialized metabolic tissues, such as liver, muscle and adipose tissue. This function has made AMPK a key therapeutic target in patients with diabetes. The connection of AMPK with several tumour suppressors suggests that therapeutic manipulation of this pathway using established diabetes drugs warrants further investigation in patients with cancer.

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Figure 1: Proteins in the liver kinase B1 and AMP-activated protein kinase complexes.Figure 2: Liver kinase B1-dependent signalling.Figure 3: AMP-activated protein kinase and PI3K signalling converge to antagonistically regulate several downstream effectors, including mTOR complex 1.Figure 4: Control of cell polarity by liver kinase B1-dependent signalling.

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Download referencesAcknowledgementsWe regret being unable to cite the work of many of our colleagues owing to space limitations. The authors thank K. Lamia for critical reading and editing of the manuscript. The authors' research is funded by grants from the National Institutes of Health (R01 DK080425 and P01 CA120964), American Cancer Society and V Foundation for Cancer Research to R.J.S. D.B.S. was supported by training grant T32 CA009370 to the Salk Institute Center for Cancer Research. R.J.S. is an early career scientist of the Howard Hughes Medical Institute.Author informationAuthors and AffiliationsDulbecco Center for Cancer Research, Molecular and Cell Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, 92037, California, USADavid B. Shackelford & Reuben J. ShawHoward Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, 92037, California, USAReuben J. ShawAuthorsDavid B. ShackelfordView author publicationsYou can also search for this author in

PubMed Google ScholarReuben J. ShawView author publicationsYou can also search for this author in

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Reuben J. Shaw.Related linksRelated linksDATABASES

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[18F] 2-fluoro-2-deoxy-D-glucose

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GlossaryPeutz–Jeghers syndrome

A disorder that is characterized by the development of gastrointestinal hamartomas and an increased predisposition to many other malignancies, including those arising in colon, breast, ovarian, pancreatic and lung tissues.

Tuberous sclerosis complex

A familial tumour syndrome that is induced through mutation of the mTOR complex 1 regulators TSC1 and TSC2.

Steatosis

Excess intracellular lipid accumulation, which can occur, for example, in the liver of patients who are diabetic or obese.

Rights and permissionsReprints and permissionsAbout this articleCite this articleShackelford, D., Shaw, R. The LKB1–AMPK pathway: metabolism and growth control in tumour suppression.

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LKB1 drives stasis and C/EBP-mediated reprogramming to an alveolar type II fate in lung cancer | Nature Communications

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LKB1 drives stasis and C/EBP-mediated reprogramming to an alveolar type II fate in lung cancer

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Published: 28 February 2022

LKB1 drives stasis and C/EBP-mediated reprogramming to an alveolar type II fate in lung cancer

Christopher W. Murray1, Jennifer J. Brady2, Mingqi Han3,4, Hongchen Cai2, Min K. Tsai

ORCID: orcid.org/0000-0003-4732-42591, Sarah E. Pierce

ORCID: orcid.org/0000-0002-9145-95591, Ran Cheng

ORCID: orcid.org/0000-0002-7617-30185,6, Janos Demeter

ORCID: orcid.org/0000-0002-7301-80555, David M. Feldser

ORCID: orcid.org/0000-0001-5975-864X7,8, Peter K. Jackson

ORCID: orcid.org/0000-0002-1742-25391,5,9,10, David B. Shackelford

ORCID: orcid.org/0000-0002-8270-898X3,4 & …Monte M. Winslow

ORCID: orcid.org/0000-0002-5730-95731,2,9,10 Show authors

Nature Communications

volume 13, Article number: 1090 (2022)

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Cancer modelsNon-small-cell lung cancerTumour-suppressor proteins

AbstractLKB1 is among the most frequently altered tumor suppressors in lung adenocarcinoma. Inactivation of Lkb1 accelerates the growth and progression of oncogenic KRAS-driven lung tumors in mouse models. However, the molecular mechanisms by which LKB1 constrains lung tumorigenesis and whether the cancer state that stems from Lkb1 deficiency can be reverted remains unknown. To identify the processes governed by LKB1 in vivo, we generated an allele which enables Lkb1 inactivation at tumor initiation and subsequent Lkb1 restoration in established tumors. Restoration of Lkb1 in oncogenic KRAS-driven lung tumors suppressed proliferation and led to tumor stasis. Lkb1 restoration activated targets of C/EBP transcription factors and drove neoplastic cells from a progenitor-like state to a less proliferative alveolar type II cell-like state. We show that C/EBP transcription factors govern a subset of genes that are induced by LKB1 and depend upon NKX2-1. We also demonstrate that a defining factor of the alveolar type II lineage, C/EBPα, constrains oncogenic KRAS-driven lung tumor growth in vivo. Thus, this key tumor suppressor regulates lineage-specific transcription factors, thereby constraining lung tumor development through enforced differentiation.

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IntroductionNeoplastic cells undergo a series of cell-state transitions throughout cancer development1,2,3,4,5. Genetic alterations, including the inactivation of tumor suppressor genes, allow cells to bypass key checkpoints that constrain the transition from normal to malignant states6. While genomic analyses of human cancers have uncovered a multitude of putative tumor suppressor genes, many of these genes have yet to be fully characterized with respect to the molecular and cellular processes that they govern to suppress tumorigenesis, including the maintenance of terminal differentiation6,7,8,9,10. The ability to globally or conditionally inactivate genes in mice has served as the basis for studying tumor suppressor function in vivo for almost three decades11,12,13,14. However, beyond demonstrating tumor-suppressive capacity and providing tumor models through which genotype-specific cellular and molecular features can be uncovered, knockout models provide limited information regarding the direct mechanisms by which tumor suppressors block tumor formation and progression15.Advances in conditional and inducible gene regulation have laid the foundation for the development of reversible genetic systems in which tumor suppressors can be inactivated and subsequently restored within established tumors in vivo15. By coupling these strategies with unbiased cellular and molecular profiling, it is possible to not only examine the consequences of tumor suppressor loss but also identify latent programs that are re-initiated upon tumor suppressor reactivation, some of which are likely critical for tumor suppression15. In addition to guiding mechanistic interrogation, in vivo tumor suppressor restoration approaches have the potential to uncover the extent to which the maintenance of a neoplastic state depends upon the sustained inactivation of a given tumor suppressor. While the dependence on oncogene activity is well-established and supported by the clinical success of oncogene-targeted therapies, the consequences of reactivating tumor suppressors are much less understood16,17. Fascinatingly, studies on some of the most frequently inactivated tumor suppressors have revealed that the restoration of different tumor suppressors in vivo drives distinct phenotypic outcomes (from complete regression after Apc restoration to inhibition of metastatic progression after Rb1 restoration)18,19,20,21,22. Thus, restoration approaches uniquely establish causal links between tumor suppressors and the processes that they govern, as well as reveal the various manners in which tumors respond to their reactivation.The tumor suppressor LKB1 (also known as serine/threonine kinase 11; STK11) is frequently inactivated in several human cancer types and governs differentiation in both normal and neoplastic settings23,24. In lung adenocarcinoma, LKB1 is genetically disrupted in 15–30% of tumors, and its deletion in mouse models of lung cancer dramatically accelerates lung tumor growth25,26. Through the manipulation of LKB1 in lung adenocarcinoma cell lines in vitro and comparative analyses between LKB1 wild-type and mutant lung tumors, many consequences of LKB1 inactivation have been identified, including oxidative and ER stress, unique metabolic dependencies and therapeutic vulnerabilities, as well as an immunosuppressive microenvironment27,28,29,30,31,32,33,34. Recent work has uncovered a role for the salt-inducible kinases (SIKs), particularly SIK1 and SIK3, as immediate downstream effectors that are critical for LKB1-mediated lung tumor suppression35,36. However, our understanding of the molecular effectors downstream of the LKB1-SIK axis that are critical for tumor suppression in vivo remains limited. Furthermore, whether the highly aggressive state that emerges as a consequence of Lkb1 deficiency can be reverted remains an outstanding question with implications for the value of therapeutic strategies to counteract specific features of the Lkb1-deficient state27,29,31,37,38.Here, we show that restoration of Lkb1 in lung tumors in vivo suppresses proliferation and induces tumor stasis. Through unbiased transcriptomic and proteomic profiling of the response to Lkb1 restoration, we uncover a requirement for LKB1 in the maintenance of alveolar type II cell identity, as well as define a connection between LKB1 activity and the induction of C/EBP target genes that are co-regulated by NKX2-1. We also demonstrate that a defining factor of the alveolar type II lineage, C/EBPα, suppresses tumor growth. Thus, we establish a link between tumor suppression in lung cancer and the activity of lineage-defining transcription factors, the disruption of which results in reversion to a progenitor-like state.ResultsGeneration of a conditionally inactivatable and restorable Lkb1

XTR alleleTo investigate the cellular and molecular processes governed by LKB1 in vivo, we generated an Lkb1XTR allele with which we could conditionally inactivate and subsequently restore Lkb1 within autochthonous tumors (Fig. 1a and “Methods”)19. We inserted an inverted gene trap cassette flanked by heterotypic pairs of mutant loxP sites and nested between FRT sites within the first intron of Lkb1. This design enables Cre-mediated stable inversion of the gene trap to intercept endogenous splicing and subsequent FLPo-ERT2-mediated deletion of the cassette upon tamoxifen administration (Fig. 1a and Supplementary Fig. 1a–d). Despite reduced levels of Lkb1 mRNA and protein in various tissues from Lkb1XTR/XTR mice as compared to Lkb1 wild-type mice, Lkb1XTR/XTR mice developed normally, were born at the expected Mendelian ratio, and did not develop gastrointestinal polyps as would be expected if the Lkb1XTR allele greatly compromised LKB1 tumor suppressor activity (Supplementary Fig. 2a–d)39. Consistent with homozygous inactivation of Lkb1 leading to embryonic lethality, we were unable to obtain Lkb1TR/TR mice upon intercrossing Lkb1TR/+ mice (generated by crossing Lkb1XTR mice to a Cre deleter line; Supplementary Fig. 2e)40,41. Furthermore, Lkb1TR/+ mice developed gastrointestinal polyps that were histologically similar to those in Lkb1null/+ mice (Supplementary Fig. 2d)39. Together, these findings demonstrate that the Lkb1XTR allele, in the expressed conformation, retains tumor-suppressive function, while the trapped Lkb1TR conformation disrupts Lkb1 expression.Fig. 1: Lkb1 restoration in established lung tumors dramatically decreases lung tumor burden.a Schematic of the XTR cassette inserted within the first intron of Lkb1 in the eXpressed, Trapped, and Restored conformations. The XTR cassette is composed of an inverted gene trap consisting of an Ad40 splice acceptor upstream of eGFP. The gene trap is flanked by heterotypic loxP sites to allow for stable Cre-mediated inversion, which results in the truncation of wild-type Lkb1 transcripts. The gene trap is nested between two FRT sites to enable FLPo-ERT2 -mediated deletion in the presence of tamoxifen, which results in the restoration of wild-type Lkb1 transcripts and LKB1 protein. b Assessment of the impact of Lkb1 restoration on tumor burden. Lung tumors were initiated in KT, KT;Lkb1XTR/XTR, and KT;Lkb1XTR/XTR;FLPo-ERT2 mice. At 6 weeks post-initiation, tumor-bearing mice were treated for 6 weeks with corn oil vehicle or tamoxifen prior to analysis. IFU infectious units, VEH vehicle, TAM tamoxifen. c Representative fluorescence (top) and hematoxylin–eosin (H&E) staining (bottom) images of tumor-bearing lungs from KT, KT;Lkb1XTR/XTR, and KT;Lkb1XTR/XTR;FLPo-ERT2 mice treated with vehicle or tamoxifen. Lung lobes within fluorescent images are outlined in white. Top scale bars = 5 mm. Bottom scale bars = 2 mm. d, e Tumor area (d) and tumor size (e) as assessed by histology for tumor-bearing KT, KT;Lkb1XTR/XTR, and KT;Lkb1XTR/XTR;FLPo-ERT2 mice at 12 weeks after tumor initiation, following 6 weeks of treatment with vehicle or tamoxifen. In d, each dot represents a mouse, while each dot in e corresponds to a tumor. Red crossbars indicate the mean. In d, KT-vehicle, n = 3 mice; KT-tamoxifen, n = 3 mice; KT;Lkb1XTR/XTR-vehicle, n = 5 mice; KT;Lkb1XTR/XTR-tamoxifen, n = 5 mice; KT;Lkb1XTR/XTR;FLPo-ERT2-vehicle, n = 4 mice; KT;Lkb1XTR/XTR;FLPo-ERT2-tamoxifen, n = 4 mice. In e, KT-vehicle, n = 11 tumors; KT-tamoxifen, n = 14 tumors; KT;Lkb1XTR/XTR-vehicle, n = 147 tumors; KT;Lkb1XTR/XTR-tamoxifen, n = 135 tumors; KT;Lkb1XTR/XTR;FLPo-ERT2-vehicle, n = 167 tumors; KT;Lkb1XTR/XTR;FLPo-ERT2-tamoxifen, n = 19 tumors. One tissue section per mouse was analyzed. P values calculated by two-sided unpaired t test. VEH vehicle, TAM tamoxifen.Full size image

Lkb1 inactivation with the Lkb1

XTR allele increases lung tumor burden and Lkb1 restoration dramatically decreases lung tumor burdenNext, we crossed the Lkb1XTR allele into the KrasLSL-G12D/+;Rosa26LSL-tdTomato (KT) background to generate KT;Lkb1XTR/XTR mice for the initiation of oncogenic KRAS-driven lung tumors after intratracheal delivery of lentiviral Cre (Supplementary Fig. 2f). Consistent with previous results using an Lkb1flox allele or CRISPR/Cas9-mediated targeting, gene trap-mediated inactivation of Lkb1 in KT;Lkb1XTR/XTR mice dramatically increased lung tumor burden relative to KT mice (Supplementary Fig. 2g–k)25,42. As anticipated, lung tumors in KT;Lkb1XTR/XTR mice were adenomas and adenocarcinomas that express NKX2-1, a marker of adenocarcinoma differentiation, with only rare clusters of poorly differentiated cancer cells at late time points (Supplementary Fig. 2l, m)36,43,44. Together, these data indicate that the Lkb1XTR allele operates as designed to disrupt Lkb1.To examine the impact of Lkb1 restoration on tumor growth, we generated KT;Lkb1XTR/XTR mice with the Rosa26FLPo-ERT2 (FLPo-ERT2) allele such that Lkb1 expression could be restored within established, Lkb1-deficient tumors upon treatment with tamoxifen (Fig. 1b). We initiated tumors in KT, KT;Lkb1XTR/XTR and KT;Lkb1XTR/XTR;FLPo-ERT2 mice with lentiviral Cre and began weekly administration of either corn oil vehicle or tamoxifen at 6 weeks after tumor initiation. Six weeks after Lkb1 restoration, tumor burden was markedly decreased in the restored context, including sevenfold fewer surface tumors, sixfold reduced total tumor area, and fourfold decreased average tumor size (Fig. 1c–e and Supplementary Fig. 3a, b). Strikingly, the tumor burden in restored mice was comparable to that of KT mice, suggesting that Lkb1 restoration at early stages of tumorigenesis dramatically impairs tumor growth. Tamoxifen treatment of KT;Lkb1XTR/XTR mice (which lack FLPo-ERT2) had no impact on tumor burden (Fig. 1c–e and Supplementary Fig. 3a, b). Lkb1 restoration at 6 weeks after tumor initiation almost doubled median survival (from 18 to 32 weeks), thus underscoring the dramatic impact of Lkb1 restoration on tumor growth (Supplementary Fig. 3c, d). Wild-type LKB1 protein was undetectable in neoplastic cells from non-restored tumors and comparable to that of Lkb1 wild-type tumors after restoration (Supplementary Fig. 3e). These findings demonstrate that established tumors remain susceptible to the tumor-suppressive activity of LKB1.To further assess the impact of Lkb1 restoration, we transplanted neoplastic cells from tumors in KT;Lkb1XTR/XTR;FLPo-ERT2 donor mice into recipient mice via intratracheal delivery (Supplementary Fig. 4a). Following a 3-week period of engraftment, recipient mice were either analyzed, treated with vehicle, or treated with tamoxifen. Analysis after an additional 5 weeks indicated that Lkb1 restoration decreased the number of tdTomatopositive surface tumors by fourfold and reduced the total tumor area by 15–25-fold relative to vehicle treatment (Supplementary Fig. 4b–d). Surprisingly, the tumor burden after five weeks of Lkb1 restoration was comparable to that of recipient mice analyzed after only the initial 3 weeks of growth (Supplementary Fig. 4b–d). Furthermore, in a separate experiment, Lkb1 restoration prior to transplantation dramatically decreased the number of tdTomatopositive surface tumors, suggesting that Lkb1 restoration might also reduce the fraction of tumor-engrafting cells (Supplementary Fig. 4e, f). These observations underscore a critical role for LKB1 in suppressing multiple aspects of lung tumor growth and tumor-engrafting capacity.Given the critical role of the p53 tumor suppressor in lung adenocarcinoma, as well as the functional link between LKB1 and the pro-apoptotic and growth-suppressive functions of p53, we determined whether concomitant inactivation of Trp53 would abrogate the growth-suppressive effects of Lkb1 restoration45,46,47,48,49. To assess the effects of restoration in the absence of p53, we initiated lung tumors in KT;Trp53flox/flox (KPT);Lkb1XTR/XTR and KPT;Lkb1XTR/XTR;FLPo-ERT2 mice and began vehicle or tamoxifen treatment at 6 weeks after tumor initiation (Supplementary Fig. 5a). After 6 weeks of Lkb1 restoration, tumor burden was significantly decreased, albeit to a lesser extent as compared to the Trp53 wild-type setting, including a twofold decrease in total lung weight and total tumor area, and a nearly fourfold reduction in average tumor size (Supplementary Fig. 5b–f, Fig. 1c–e, and Supplementary Fig. 3a, b). The reduced impact of Lkb1 restoration in the context of Trp53-deficiency could result from more rapid tumor growth, progression prior to restoration, and/or a partial requirement for p53 in LKB1-driven growth arrest.

Lkb1 restoration impairs lung tumor growth and decreases glucose avidityGiven the dramatic effect of Lkb1 restoration on lung tumor burden, we examined the impact of Lkb1 restoration on the dynamics of lung tumor growth by performing longitudinal micro-computed tomography (µCT) imaging on restored and non-restored tumors. We initiated tumors in KT;Lkb1XTR/XTR and KT;Lkb1XTR/XTR;FLPo-ERT2 mice with lentiviral Cre, began weekly treatment with either vehicle or tamoxifen upon detection of lung nodules (which ranged from 17 to 21 weeks after tumor initiation), and tracked tumor volume by µCT for 6–10 weeks (Fig. 2a and Supplementary Fig. 6a). While non-restored tumors continued to grow, restored tumors were arrested (Fig. 2b, c and Supplementary Fig. 6b). Histological examination revealed that Lkb1 restoration greatly reduced tumor burden, including a sevenfold decrease in total tumor area and a fivefold reduction in individual tumor size (Supplementary Fig. 6c, d). These data demonstrate that the restoration of Lkb1, unlike other tumor suppressors, results in profound tumor stasis without regression.Fig. 2: Lkb1 restoration drives tumor stasis and suppresses the increase in glucose avidity that accompanies progression.a Longitudinal µCT imaging of lung tumors in KT;Lkb1XTR/XTR and KT;Lkb1XTR/XTR;FLPo-ERT2 mice. Treatment began within 1 to 6 weeks from initial detection of lung tumors. Tumors were tracked for an additional 6–10 weeks, and lung tissue was harvested at 28 weeks. VEH vehicle, TAM tamoxifen. b Changes in tumor volume. Red numbers indicate the number of tumors measured at a given time point. Bars correspond to the mean tumor volume relative to size at first detection. Error bars indicate standard deviation. Source data is displayed in Supplementary Fig. 6b. KT;Lkb1XTR/XTR-tamoxifen, n = 10 tumors; KT;Lkb1XTR/XTR;FLPo-ERT2-vehicle, n = 9 tumors; KT;Lkb1XTR/XTR;FLPo-ERT2-tamoxifen, n = 10 tumors. c Representative µCT images of tumor-bearing lungs at treatment initiation (top) and after 10 weeks of treatment (bottom). d BrdU (top) and cleaved caspase 3 (CC3; bottom) detection by IHC within Lkb1 non-restored (left) and restored (right) lung tumors following 2 weeks of treatment with vehicle or tamoxifen. Inset image shows CC3 staining of involuting mammary gland. Scale bars = 100 µm. Images were acquired from a single experiment including multiple biological replicates as noted in e, f. e, f Quantification of BrdU+ (e) and CC3+ (f) cells within Lkb1-restored and non-restored tumors. Each dot represents a ×20 field. Red crossbars indicate the mean. In e, KT;Lkb1XTR/XTR-vehicle, n = 60 fields; KT;Lkb1XTR/XTR-tamoxifen, n = 60 fields; KT;Lkb1XTR/XTR;FLPo-ERT2-vehicle, n = 60 fields; KT;Lkb1XTR/XTR;FLPo-ERT2-tamoxifen, n = 80 fields. In f, KT;Lkb1XTR/XTR-vehicle, n = 60 fields; KT;Lkb1XTR/XTR-tamoxifen, n = 80 fields; KT;Lkb1XTR/XTR;FLPo-ERT2-vehicle, n = 80 fields; KT;Lkb1XTR/XTR;FLPo-ERT2-tamoxifen, n = 120 fields. One tissue section per mouse was analyzed. P values calculated by two-sided unpaired t test. HPF high-power field, VEH vehicle, TAM tamoxifen. g Serial 18F-FDG-PET/CT imaging. Tamoxifen treatment of KT;Lkb1XTR/XTR, and KT;Lkb1XTR/XTR;FLPo-ERT2 mice began within 2 days of establishing baseline levels of 18F-FDG uptake (at least two measurements within 18–24 weeks after tumor initiation). 18F-FDG uptake was captured after 2 and 6 weeks of treatment, as well as at 12 weeks for restored mice. h Changes in 18F-FDG uptake in restored (n = 15 tumors) and non-restored (n = 22 tumors) tumors. Source data displayed in Supplementary Fig. 8c. P values calculated by two-sided unpaired t test.Full size imageTo determine at the cellular level how Lkb1 restoration drives tumor stasis, we examined markers of proliferation (BrdU incorporation and Ki-67) and cell death (cleaved caspase 3) by immunohistochemistry 2 weeks following Lkb1 restoration (Supplementary Fig. 7a). Lkb1-restored tumors were significantly less proliferative as compared to non-restored tumors, without evidence of increased cell death (Fig. 2d–f and Supplementary Fig. 7b, c). Consistently, Lkb1 restoration in lung cancer cell lines derived from tumors from KPT;Lkb1XTR/XTR;FLPo-ERT2 mice resulted in a significant decrease in the fraction of cells in S phase and variable effects on the rate of cell death after Lkb1 restoration (Supplementary Fig. 7d–g). Thus, the induction of tumor stasis by Lkb1 restoration is likely driven by suppression of proliferation.Lkb1 loss has been previously linked to enhanced glucose uptake in mouse and human lung tumors as well as an increased glycolytic flux in human lung cancer cells in vitro50,51. To monitor changes in glucose uptake in response to Lkb1 restoration, we performed serial positron emission tomography with 2-deoxy-2-[fluorine-18]fluoro-D-glucose integrated with computed tomography (18F-FDG-PET/CT) imaging (Fig. 2g and Supplementary Fig. 8a). Tumors were initiated in KT;Lkb1XTR/XTR and KT;Lkb1XTR/XTR;FLPo-ERT2 mice with lentiviral Cre, and mice were treated with tamoxifen after establishing a baseline of 18F-FDG uptake (two consecutive measurements of 18F-FDG uptake). Within 2 weeks of starting tamoxifen treatment, restored tumors had reduced uptake relative to pre-treatment levels, while non-restored tumors trended towards increased 18F-FDG uptake (Fig. 2h and Supplementary Fig. 8b, c). Six weeks after treatment initiation, 18F-FDG uptake had increased nearly twofold relative to pre-treatment among non-restored tumors, whereas it remained largely unchanged in the Lkb1-restored context. Even 12 weeks after Lkb1 restoration, 18F-FDG uptake remained unchanged (Fig. 2h and Supplementary Fig. 8c). These data demonstrate that Lkb1 restoration induces tumor stasis and abrogates the increase in glucose avidity that coincides with tumor progression.

Lkb1 restoration drives transcriptional programs relating to alveolar type II cell functionsTo uncover the molecular processes governed by LKB1 in vivo, we performed RNA-seq on neoplastic cells that were isolated by FACS from restored and non-restored lung tumors 2 weeks after starting tamoxifen treatment, as well as Lkb1 wild-type tumors from KT mice (Fig. 3a and Supplementary Data 1–4). The expression of Lkb1 was negligible in non-restored tumors, but comparable in restored and Lkb1 wild-type tumors (Supplementary Fig. 9a). Comparison of non-restored to KT tumors revealed that the gene expression differences were similar to published comparisons of Lkb1-deficient and Lkb1-proficient mouse lung tumors (Supplementary Fig. 9b). Furthermore, cancer cells from non-restored tumors had many established transcriptional features of the Lkb1-deficient state, including higher expression of gene sets relating to angiogenesis, hypoxia, adhesion, and epithelial-mesenchymal transition (Supplementary Fig. 9c)25,35,36,43,52,53.Fig. 3: Lkb1 restoration drives programs related to alveolar type II epithelial cell functions in lung adenocarcinoma.a Profiling the acute transcriptional response to Lkb1 restoration within established lung tumors. Mice were treated with vehicle or tamoxifen for 2 weeks prior to fluorescence-activated cell sorting (FACS)-isolation of tdTomatopositive neoplastic cells for RNA-seq analysis. KT, n = 4 mice; KT;Lkb1XTR/XTR-tamoxifen, n = 3 mice; KT;Lkb1XTR/XTR;FLPo-ERT2-vehicle, n = 3 mice; KT;Lkb1XTR/XTR;FLPo-ERT2-tamoxifen, n = 4 mice. VEH vehicle, TAM tamoxifen. b Hierarchical clustering of the transcriptional profiles of Lkb1 wild-type (KT), non-restored, and restored tumors by Euclidean distance. c Heatmap of genes that vary significantly (FDR < 0.05; likelihood ratio test). Lkb1 is indicated. K-means clustering defined sets of genes that change concordantly across all samples (left). d Transcription factor motifs enriched within the putative promoters (−450 to +50 bp from transcription start site) of those genes that are higher (log2 Fold Change >1 and FDR < 0.05) in restored lung tumors relative to non-restored using the JASPAR 2018 collection of position frequency matrices. e Expression of markers associated with alveolar type II epithelial cell identity across Lkb1 wild-type, non-restored, and restored tumors. f–h GSEA using signatures of ATII identity derived from previously published single-cell RNA-seq datasets (f) and the Gene Ontology (GO) Biological Process module (g, h), illustrating the enrichment of gene sets among those genes that are higher in restored relative to non-restored tumors. Groups of enriched gene sets relating to lipid metabolism and transport (g) as well as immunomodulation (h) are shown. The size of the dots corresponds to the number of core enrichment genes and the fill color reflects FDR.Full size imageTo understand how the Lkb1-restored state relates to the KT and non-restored states, we performed hierarchical clustering and principal component analysis. Hierarchical clustering revealed that restored tumors co-segregated with KT tumors away from non-restored tumors (Fig. 3b). By principal component analysis, Lkb1 wild-type, non-restored, and restored tumors were separated across the first principal component (Supplementary Fig. 9d). Lkb1-restored tumors clustered at an intermediate position between KT and non-restored tumors, indicating that the acute response to Lkb1 restoration results in partial reversion to a transcriptional state that remains distinct from tumors that were Lkb1-proficient throughout their development (Supplementary Fig. 9d). Genes with the lowest loading coefficients with respect to the first principal component (i.e. genes that are highest in KT tumors relative to restored and non-restored tumors) were enriched for gene sets relating to chemotaxis, extracellular structure organization, protein secretion, and steroid metabolism (Supplementary Fig. 9e). These programs are reminiscent of the surfactant production and immunomodulatory functions of ATII cells, which are thought to be a major cell type of origin for oncogenic KRAS-driven lung adenocarcinoma54,55,56. In contrast, the genes with the highest loading coefficients within the first principal component were enriched for gene sets relating to proliferation, adhesion, and extracellular matrix interactions, which are processes that have been linked to early progenitors of the distal lung epithelium (Supplementary Fig. 9e)54. These observations suggest that LKB1 activity may govern a transition between cycling progenitor-like and non-cycling ATII-like states.Next, we performed k-means clustering to identify sets of genes that change concordantly across all samples (Fig. 3c). Genes that were higher in both restored and Lkb1 wild-type tumors were enriched for gene sets related to antigen presentation and lipid metabolism, which are again consistent with established ATII cell functions (Supplementary Fig. 10a)57,58. Genes relating to angiogenesis and adhesion were specifically higher in non-restored tumors (Supplementary Fig. 10a). Apart from these changes at the global level, direct comparison of restored and non-restored tumors suggested that LKB1 reduces proliferation- and glycolysis-related genes, which agrees with our IHC and 18F-FDG-PET/CT results (Supplementary Fig. 10b–d). Furthermore, genes relating to mTOR signaling were lower in restored tumors, which is consistent with a canonical function of LKB1 in inhibiting mTOR complex 1 via activation of AMPK (Supplementary Fig. 10e)59. Together, these initial findings highlight transcriptional changes reflecting reduced proliferation and altered metabolism in response to Lkb1 restoration, as well as increased expression of genes relating to specialized functions of ATII cells.

Lkb1 restoration rescues features of alveolar type II identityTo identify potential mediators of the transcriptional changes induced by Lkb1 restoration, we performed motif enrichment analysis. Among the promoters of those genes that are higher within restored tumors, there was a significant enrichment of C/EBP motifs (83 of the 128 LKB1-induced genes had C/EBPα motifs within their promoters) (Fig. 3d). Members of the C/EBP family of transcription factors coordinate proliferation and differentiation in multiple tissue contexts60,61. In particular, C/EBPα activity is required for ATII differentiation, suggesting that LKB1 may operate upstream of C/EBP factors to drive ATII differentiation62,63. Complementary to these findings, Sp/Klf motifs were enriched among genes that were higher in non-restored tumors (Supplementary Fig. 10f). Sp/Klf activity is enriched in alveolar epithelial progenitors and a regenerative subset of ATII cells, suggesting that Lkb1 inactivation leads to loss of ATII differentiation and reversion to a progenitor-like state64,65.Consistent with LKB1 maintaining ATII differentiation, restored tumors, like their Lkb1 wild-type counterparts, had higher expression of several ATII markers relative to non-restored tumors, and multiple signatures of ATII identity were highly enriched in the restored state (Fig. 3e, f)54,66,67,68,69,70,71,72. Gene set enrichment analysis (GSEA) also revealed modest enrichment of signatures of ATII identity in KT tumors as compared to Lkb1-restored tumors and significant enrichment of signatures relating to morphogenesis within Lkb1-restored. This suggests that the non-overlapping nature of Lkb1-restored and Lkb1 wild-type transcriptional states by PCA is attributable to varying degrees of ATII-like differentiation and the activity of broader developmental programs (Supplementary Fig. 10g, h). The induction of ATII markers by Lkb1 restoration was conserved even in the absence of p53 (Supplementary Fig. 11a–f and Supplementary Data 1 and 5). Consistent with the role of SIKs as critical effectors of LKB1-mediated tumor suppression in the lung, mouse lung tumors with CRISPR/Cas9-mediated targeting of Siks also had lower expression of several ATII markers, suggesting that the LKB1-SIK axis maintains ATII identity (Supplementary Fig. 11g)35,36. Notably, a subset of ATII markers, including SFTPA1, CXCL15, LYZ2, and HC, were also higher at the protein level within restored tumors relative to non-restored tumors (Supplementary Fig. 12a–f and Supplementary Data 6 and 7). Taken together, these findings suggest that LKB1 maintains ATII identity and that Lkb1 restoration induces features of ATII cells within established lung tumors.Beyond specific markers of ATII identity, we also noted the upregulation of processes relating to ATII functions in response to Lkb1 restoration. Gene sets pertaining to lipid metabolism and export as well as immunomodulation, were higher in restored tumors as compared to non-restored tumors at the mRNA level (Fig. 3g, h)54. At the protein level, lipid metabolism gene sets were enriched among the proteins that were more abundant in restored tumors, which is consistent with the lipid-processing functions required for surfactant production by mature ATII cells (Supplementary Fig. 12g). Additionally, there was an enrichment of mitochondrial proteins involved in oxidative phosphorylation among the proteins higher in restored tumors, which agrees with previous work demonstrating increased mitochondrial respiration capacity upon re-expressing LKB1 in human lung cancer cells (Supplementary Fig. 12g)59. Furthermore, mitochondrial function is tightly linked to lipid metabolism in ATII cells, as mitochondria generate intermediates for the synthesis of phospholipids that are required for surfactant production73,74. Collectively, our transcriptomic and proteomic profiling of the acute response to Lkb1 restoration in vivo indicates that Lkb1 inactivation leads to the loss of ATII differentiation, which is rapidly reversible upon Lkb1 restoration.The acute response to Lkb1 restoration predominantly impacts the neoplastic epithelial compartmentExtending from our observation that Lkb1 restoration re-establishes features of ATII identity, we sought to understand whether Lkb1 restoration modulates the cellular composition of lung tumors. To uncover changes in cellular state and/or abundance both within and outside of the neoplastic compartment, we performed single-cell RNA-seq on cells dissociated from lung tumors of KT;Lkb1XTR/XTR and KT;Lkb1XTR/XTR;FLPo-ERT2 mice following 2 weeks of tamoxifen treatment (Supplementary Fig. 13a and “Methods”). Across all tumors, we observed diverse populations of immune, stromal, and neoplastic epithelial cells (Supplementary Fig. 13b, c). Apart from a fivefold change in the relative abundance of a rare population of putative mast cells, short-term Lkb1 restoration did not significantly alter the abundance of immune and stromal cell clusters (Supplementary Fig. 13d). The lack of change in the abundance of infiltrating neutrophil and T cells was notable given that Lkb1 inactivation in lung tumors has been associated with increased neutrophil recruitment and decreased T cell infiltration31. Our results could stem from the relatively short time period after Lkb1 restoration and/or be due to the fact that these indicators of an immunosuppressive microenvironment have been more clearly linked to the adenosquamous histotype, which does not develop in this mouse model29,36,52.To uncover gene expression changes within each cellular compartment that may reflect cell-state changes induced by Lkb1 restoration, we collapsed each cluster into pseudobulk samples and performed differential gene expression analysis between restored and non-restored samples. Apart from a global increase in Lkb1 due to the removal of the XTR gene trap within all cellular compartments, the most extensive gene expression changes occurred within the neoplastic epithelial compartment (Supplementary Fig. 13e-g). Focused examination of the neoplastic compartment revealed three sub-clusters, including ATI-like, ATII-like, and an “indeterminate” ATII-like subpopulation, which had attenuated expression of ATII markers (Supplementary Fig. 14a, b). Stratification of the neoplastic compartment on the basis of Lkb1 status uncovered an enrichment of the indeterminate cluster within non-restored tumors and the ATII-like cluster in restored tumors (Supplementary Fig. 14c). Thus, in agreement with our bulk analyses, Lkb1 activity appears to drive neoplastic cells into a mature ATII cell state.Neoplastic cells exist across a cell state spectrum resembling the progression from ATII to ATI identitiesTo more thoroughly interrogate the cell states within the neoplastic compartment, we performed single-cell RNA-seq on tdTomatopositive neoplastic cells sorted from restored and non-restored lung tumors (Fig. 4a and Supplementary Fig. 15a). Across all tumors, we observed four major clusters of cells and a minor cluster of highly proliferative cells (Fig. 4b, c). The largest cluster expressed markers of ATII cells, such as Lyz2, Sftpa1, Hc, and Cxcl15 (Fig. 4c)54,75. As noted in our initial single-cell analysis, there also existed an “indeterminate” ATII-like cluster. The remaining two clusters resembled the ATI state, with the larger of the two expressing established ATI markers, including Ager and Hopx (Fig. 4c)54,75. In contrast, the smaller ATI-like cluster had high expression of Krt8 and Krt19, which delineate a “stalled” ATII-ATI transitional state that emerges following lung injury (Fig. 4c)64,66,76.Fig. 4: Lkb1 restoration enforces an alveolar type II-like cell state.a Profiling the acute transcriptional response to Lkb1 restoration within established tumors at single-cell resolution. KT;Lkb1XTR/XTR-vehicle, n = 1 mouse; KT;Lkb1XTR/XTR-tamoxifen, n = 1 mouse; KT;Lkb1XTR/XTR;FLPo-ERT2-vehicle, n = 1 mouse; KT;Lkb1XTR/XTR;FLPo-ERT2-tamoxifen, n = 3 mice. b Single-cell RNA-seq on tdTomatopositive neoplastic cells from Lkb1-restored and non-restored tumors. Cell fill reflects assignment to clusters defined by the Louvain algorithm. c Top ten markers that define each of the neoplastic cell clusters. The predicted cell type identities are listed to the left. Louvain cluster assignments are indicated by the bars at the top of the heatmap. d RNA velocity analysis on neoplastic cells. Velocity vectors are summarized as streamlines overlaid on UMAP embeddings. The general direction of flow follows that of the ATII-ATI differentiation axis, with the indeterminate cluster residing at an intermediate position. e Trajectory inference analysis on sorted neoplastic cells. Cell fill corresponds to its relative position in pseudotime. The pseudotime trajectory runs along the ATII-ATI differentiation axis, with the indeterminate cluster residing at an intermediate position. f Proportion of each neoplastic epithelial subpopulation within Lkb1-restored and non-restored tumors. Fill reflects Louvain cluster assignments, and their corresponding predicted identities are listed. Each column corresponds to an individual animal. g GSEA comparing cells of the ATII-like and indeterminate clusters at the pseudobulk level using the Hallmarks module. The size of dots corresponds to the number of core enrichment genes and the fill color reflects FDR. The plotted gene sets correspond to those that were enriched among the genes that are higher in the indeterminate cluster relative to the ATII-like cluster. h Expression of Sox9 across the five Louvain clusters. Predicted cluster identities are listed (left). Fill indicates average expression and dot size reflects the proportion of cells within a given cluster that express Sox9.Full size imageTo elucidate the relationship between the indeterminate subpopulation and the other subpopulations, we performed dynamic inference analyses. Both RNA velocity analysis and pseudotemporal ordering suggested that the indeterminate cluster arises from the ATII-like cluster and represents an intermediate state along with the progression from ATII to ATI states, which resembles ATII-ATI trans-differentiation that occurs in response to lung injury (Fig. 4d, e)64,66,76. Consistent with the Krt8+/Krt19+ population representing a stalled transitional state during ATII-ATI trans-differentiation, this cluster branches off from the ATII-ATI primary trajectory (Fig. 4e and Supplementary Fig. 15b)66,76. These findings indicate that the neoplastic compartment comprises several identities that resemble the spectrum of states that emerge during ATII-ATI trans-differentiation, including an indeterminate subpopulation that likely arises from the ATII-like population and may represent an intermediate transition state.LKB1 drives neoplastic cells toward an ATII-like cell stateUpon stratification of the scRNA-seq dataset into Lkb1-restored or non-restored tumors, we uncovered a striking shift from the indeterminate state within non-restored tumors to the ATII-like state within restored tumors (a 14-fold increase in the proportion of ATII-like cells and an 8-fold reduction in indeterminate cells within restored tumors as compared to non-restored tumors) (Fig. 4f). We also observed significant concordance between our single-cell and bulk RNA-seq datasets in terms of the gene expression changes induced by Lkb1 restoration (Supplementary Fig. 15c, d). Notably, relative to restored tumors, the proportion of actively proliferating cells identified by elevated expression of genes relating to cell cycle progression was greater within non-restored tumors, and cells derived from non-restored tumors were significantly over-represented within the actively proliferating population (Fig. 4f and Supplementary Fig. 15e). Upon regression of variation due to cell cycle-driven gene expression changes, we observed that the ATII-like subpopulation was under-represented among cells that were initially identified as actively proliferating, suggesting that the ATII-like state is less proliferative relative to the other subpopulations (Supplementary Fig. 15f). Notably, the fraction of proliferative cells was reduced in Lkb1-restored tumors as compared to non-restored tumors across each of the subpopulations, suggesting that the growth-suppressive response to LKB1 activity extends beyond the indeterminate state (Supplementary Fig. 15g). Collectively, these analyses indicate that Lkb1 restoration drives the transition from an indeterminate state to a more differentiated and less proliferative ATII-like state.To identify molecular features that distinguish the indeterminate state and potentially uncover the mechanism by which it emerges as a consequence of Lkb1 inactivation, we compared the gene expression profiles of the ATII-like and indeterminate clusters (Supplementary Fig. 15h). GSEA revealed that gene sets relating to proliferation, EMT, hypoxia, and KRAS signaling were higher in the indeterminate subpopulation (Fig. 4g). In agreement with our bulk RNA-seq analysis, C/EBP motifs were enriched within the promoters of genes that are higher in the ATII-like cluster, as well as an enrichment of ATII signatures, indicating that the indeterminate cluster represents a C/EBP-low state lacking features of ATII differentiation (Supplementary Fig. 15i, j)54,66,67,68,69,70,71,72. Furthermore, Sp/Klf motifs and signatures of ATI identity were enriched among the genes that were higher in the indeterminate cluster, consistent with the indeterminate population representing a progenitor-like state that arises as a consequence of the loss of ATII differentiation (Supplementary Fig. 15j, k)64,65. Sox9, which is a marker delineating distal tip progenitor cells that give rise to the alveolar lineages and also an inhibitor of alveolar differentiation, was more highly expressed in the indeterminate cluster as compared to the ATII-like state (Fig. 4h)77,78. The indeterminate subpopulation also had increased Wnt5a expression, which has been shown to potentiate the mitogenic activity of epidermal growth factor in ATII cells (Supplementary Fig. 15l)79. Taken together, these findings demonstrate that Lkb1 restoration reinstates ATII-like differentiation, driving cells away from a C/EBP-low, progenitor-like state that emerges as a consequence of Lkb1 inactivation.C/EBP transcription factors suppress lung tumor growthTo investigate whether C/EBP transcription factors and a subset of genes exhibiting LKB1-dependent expression function as tumors suppressors, we integrated CRISPR/Cas9 with tumor barcoding and high-throughput barcode sequencing (Tuba-seq) to assess the impact of inactivating candidate genes on tumor growth42. Of the six members within the C/EBP family, we focused on those paralogs that are most highly expressed within oncogenic KRAS-driven lung tumors (Supplementary Fig. 16a), excluding the inhibitory paralog, C/EBPγ (Cebpg), and C/EBPζ (Ddit3), which redirects C/EBP activity from canonical target genes80,81,82,83. To inactivate each candidate gene in a multiplexed format, we initiated tumors in KT and KT;H11LSL-Cas9 mice using a pool of Lenti-sgRNA/Cre vectors that include two-component barcodes comprised of sgRNA and clonal identifiers (sgID-BC) (Fig. 5a and Supplementary Fig. 16b)42. Fourteen weeks after tumor initiation, we quantified distributions of tumor size across each genotype by deep sequencing of the sgID-BC region that had been amplified from the integrated lentiviral genomes within bulk tumor-bearing lungs (Supplementary Fig. 16b)42. Strikingly, simultaneous targeting of Cebpa, Cebpb, and Cebpd significantly increased tumor growth, while the inactivation of other LKB1-dependent genes had no significant impact on tumor growth (Fig. 5b and Supplementary Fig. 16c). In conjunction with our observations that C/EBP activity is increased upon Lkb1 restoration, these findings suggest that C/EBP transcription factors may be critical effectors of LKB1-mediated tumor suppression.Fig. 5: C/EBP transcription factors constrain oncogenic KRAS-driven lung tumor growth.a Interrogation of the tumor-suppressive capacity of a series of LKB1-dependent genes and C/EBP transcription factors (targets listed in Supplementary Fig. 16b). Lenti-sgRNA/Cre vectors targeting each candidate gene were pooled prior to delivery into KT and KT;H11LSL-Cas9 mice (method outlined in Supplementary Fig. 16b). b Bulk tumor-bearing lungs were analyzed by Tuba-seq. Percentile plot depicting tumor size at several percentiles relative to the distribution of tumors initiated with Lenti-sgRNA/Cre vectors encoding inert sgRNAs (sgNeo1, sgNeo2, sgNeo3, sgNT1, sgNT2). Lkb1 and C/ebp family targeting vectors are shown. Each vector has a distinct fill color, and fill saturation indicates percentile. Colored fill indicates that tumor size at a given percentile is significantly different from inert sgRNAs, while grayscale indicates no significant difference. Error bars indicate 95% confidence intervals centered on the mean of relative tumor size at a given percentile. c Validation of C/EBP factors as suppressors of oncogenic KRAS-driven tumor growth in a non-multiplexed format. Tumors were initiated in KT and KT;H11LSL-Cas9 mice with either Lenti-sgInert/Cre (sgNeo1/sgNT1/sgNeo2; sgInert) or Lenti-sgCebpa/b/d/Cre (sgCebpa/sgCebpb/sgCebpd; sgCebpa/b/d). N = 5 mice per genotype-virus cohort. d Representative fluorescence (top) and H&E (bottom) images of tumor-bearing lungs from KT and KT;H11LSL-Cas9 mice transduced with either Lenti-sgInert/Cre or Lenti-sgCebpa/b/d/Cre. Lung lobes within fluorescent images are outlined in white. N = 5 mice per genotype-virus cohort. Top scale bars = 5 mm. Bottom scale bars = 2 mm. e, f Quantification of tumor area (e) and tumor size (f) by histological examination of tumor-bearing lungs from KT and KT;H11LSL-Cas9 mice transduced with either Lenti-sgInert/Cre or Lenti-sgCebpa/b/d/Cre. Each dot represents either individual mice (e) or individual tumors (f). Red crossbars indicate the mean. In e, n = 5 mice per genotype-virus cohort. One tissue section per mouse was analyzed. In f, KT-sgInert, n = 22 tumors; KT-sgCebpa/b/d, n = 23 tumors; KT;H11LSL-Cas9-sgInert, n = 58 tumors; KT;H11LSL-Cas9-sgCebpa/b/d, n = 167 tumors. P values were calculated by a two-sided unpaired t test.Full size imageTo validate the tumor-suppressive capacity of C/EBP factors, we initiated tumors in KT and KT;H11LSL-Cas9 mice with either Lenti-sgNeo1-sgNT-sgNeo2/Cre (Lenti-sgInert/Cre) or Lenti-sgCebpa-sgCebpb-sgCepbd/Cre (Lenti-sgCebpa/b/d/Cre) (Fig. 5c). CRISPR/Cas9-mediated targeting of C/ebp factors increased overall tumor burden in terms of the total tumor area and individual tumor size (Fig. 5d–f and Supplementary Fig. 16d). Together, these data indicate that C/EBP factors constrain oncogenic KRAS-driven lung tumor growth in vivo.Inactivation of C/ebp transcription factors recapitulates transcriptional features of Lkb1 deficiencyGiven that genes induced by LKB1 activity were enriched with C/EBP motifs, we determined the extent to which the transcriptional changes elicited by Lkb1 inactivation can be attributed to reduced C/EBP activity. To compare the transcriptional profiles of Lkb1- and C/ebp-targeted tumors, we performed RNA-seq on neoplastic cells sorted from tumors initiated in KT;H11LSL-Cas9 mice with Lenti-sgInert/Cre, Lenti-sgCebpa/b/d/Cre, or Lenti-sgLkb1/Cre (Supplementary Fig. 17a and Supplementary Data 8–11). Principal component analysis and hierarchical clustering separated C/ebp- and Lkb1-targeted tumors from tumors initiated with sgInert, suggesting conserved transcriptional changes in C/ebp- and Lkb1-targeted tumors (Supplementary Fig. 17b, c). Among the genes that vary significantly across the dataset, we defined six groups by k-means clustering (Fig. 6a). The genes that were higher in both C/ebp- and Lkb1-targeted tumors relative to sgInert tumors (354 of the 1823 variable genes) were enriched for genes relating to extracellular matrix interactions, migration, adhesion, and respiratory development (Fig. 6a and Supplementary Fig. 17d). Conversely, the genes that were lower in C/ebp- and Lkb1-targeted tumors (352 of the 1823 variable genes) were enriched for genes relating to translation and sterol biosynthesis (Fig. 6a and Supplementary Fig. 17d). Notably, several markers of ATII identity were lower in C/ebp-targeted and Lkb1-targeted tumors, consistent with the loss of ATII differentiation upon inactivation of C/ebp factors or Lkb1 (Fig. 6a). Furthermore, by GSEA, we found that C/EBP-dependent genes were enriched among those genes that were higher in the ATII-like neoplastic subpopulation (Fig. 6b). Moreover, genes that were higher in C/ebp-targeted tumors were enriched among the genes that were higher within the indeterminate population, thus reinforcing the notion that the indeterminate state corresponds to progenitor-like cells exhibiting low C/EBP activity (Fig. 6b). These analyses uncovered shared transcriptional changes upon inactivation of either C/ebp factors or Lkb1, suggesting that C/EBPs may operate downstream of LKB1 to suppress tumor growth and maintain ATII identity.Fig. 6: C/EBP transcription factors co-regulate a subset of LKB1-dependent genes.a Transcriptional profiling of Lkb1- and C/ebp-targeted tumors as well as oncogenic KRAS-only tumors (sgInert). Genes that vary significantly (FDR < 0.05; likelihood ratio test). Markers of alveolar type II identity are indicated. b Enrichment of C/EBP-dependent genes (top) among genes that are higher in the ATII-like state. Enrichment of genes that are higher in C/ebp-targeted tumors (bottom) among genes that are higher in the indeterminate state. ES Running enrichment score. NES normalized enrichment score, FC fold change. c, d Comparison of genes that are higher (c) or lower (d; absolute log2 Fold Change >1 and FDR < 0.05) in Lkb1- or C/ebp-targeted tumors relative to tumors driven by oncogenic KRAS alone (sgInert). P values from hypergeometric tests are indicated. e Transcription factor motif enrichment on genes that are either uniquely lower (log2 Fold Change < −1 and FDR < 0.05) in Lkb1- (left) or C/ebp-targeted tumors (middle) relative to sgInert tumors or are jointly LKB1- and C/EBP-dependent (right). f Proportion of genes proximal to NKX2-1 binding sites (within −3 to +1 kb from TSS) among those that are jointly dependent upon LKB1 and C/EBPs (log2 Fold Change < −0.5 and FDR < 0.05). P value from hypergeometric test is indicated. Derived from previously published NKX2-1 ChIP-seq dataset85. g Transcriptional comparison of Nkx2-1-deficient and Nkx2-1-proficient lung tumors using previously published gene expression data86. Genes that are jointly dependent upon LKB1 and C/EBPs (log2 Fold Change < −0.5 and FDR < 0.05) are plotted. Blue fill denotes genes that are dependent upon NKX2-1(log2 Fold Change < −0.5 and FDR < 0.05). Shape indicates proximal binding of NKX2-1 (within −3 to +1 kb from TSS). The number of NKX2-1-bound genes that are or are not NKX2-1-dependent is indicated. h Proposed model for the function of LKB1 in lung tumors. Lkb1 inactivation enables the emergence of neoplastic cell states outside of ATII-like identity. Upon Lkb1 restoration, progenitor-like cells assume a more mature, less proliferative ATII-like identity, reflecting the increased activity of the lineage-defining factor, C/EBPα (left). At the molecular level (right), C/EBP operates indirectly downstream of LKB1-SIK in cooperation with NKX2-1 and other transcription factors to drive ATII differentiation.Full size imageTo further examine the extent of conservation of transcriptional changes upon inactivation of either C/ebp factors or Lkb1, we directly compared differentially expressed genes and pathways relative to sgInert tumors. In both C/ebp- and Lkb1-targeted contexts, there was a highly significant overlap in terms of genes that were lower or higher relative to tumors initiated with sgInert (Fig. 6c, d and Supplementary Fig. 17e). Among the genes that were lower in either C/ebp- or Lkb1-targeted tumors, there was a significant enrichment of genes with upstream C/EBP motifs (with 76 out of 121 promoters of LKB1-dependent genes and 121 out of 230 promoters of C/EBP-dependent genes containing C/EBPα motif), consistent with our previous observation of C/EBP activity downstream of LKB1 (Supplementary Fig. 17f). C/ebp- and Lkb1-targeted tumors also exhibit overlap in terms of enriched gene sets, particularly those relating to adhesion, migration, and extracellular matrix interaction (Supplementary Fig. 17g). In conjunction with increased expression of putative C/EBP target genes in response to Lkb1 restoration, these findings indicate that C/ebp inactivation elicits transcriptional changes that resemble Lkb1 deficiency and suggest that C/EBPs function downstream of LKB1.A subset of LKB1- and C/EBP-dependent genes are NKX2-1 target genesWhile there was significant concordance in the gene expression changes elicited by inactivating either Lkb1 or C/ebp factors, not all genes were regulated by both C/EBPs and LKB1, suggesting more nuanced regulation of C/EBP targets by LKB1 signaling. Comparison with the gene expression changes elicited by Sik targeting indicated significant but incomplete overlap with those changes induced by C/ebp targeting, suggesting that the link between C/EBPs and the LKB1-SIK axis is unlikely to be strictly linear (Supplementary Fig. 17h). To identify potential transcription factors downstream of LKB1 that could cooperate with C/EBPs, we performed motif enrichment on subsets of genes that were uniquely or jointly dependent on LKB1 or C/EBPs. Interestingly, among those genes that were jointly dependent on LKB1 and C/EBPs, there was a significant enrichment for motifs belonging to TATA-binding protein, bHLH factors (FIGLA and MSC), the HNF family, as well as the NKX2 family (33 out of 51 promoters analyzed had NKX2 motifs) (Fig. 6e). C/EBPα has been proposed to direct ATII-specific, NKX2-1-driven transcriptional programs within the distal lung epithelium84. Consistent with the concerted action of C/EBPα and NKX2-1, C/EBP motifs were also highly enriched at NKX2-1-bound sites from previous ChIP-seq data from oncogenic KRAS-driven lung tumors (Supplementary Fig. 17i)85. Furthermore, NKX2-1 binds proximal to 86% of genes that are dependent on both LKB1 and C/EBP (Fig. 6f). Of the C/EBP- and LKB1-dependent, NXK2-1-bound genes, nearly half exhibit NKX2-1-dependent expression, suggesting that NKX2-1 may cooperate with C/EBP factors to drive a subset of LKB1-dependent genes (Fig. 6g)86. Notably, among this subset were several markers of ATII identity, including Etv5, Cxcl15, Hc, Lyz2, thus underscoring the role of the concerted action of LKB1 and C/EBPs in maintaining ATII identity. Deconvolution of C/EBP-mediated tumor suppression through a secondary Tuba-seq screen indicated no evidence of functional redundancy among the C/EBP paralogs, with C/EBPα being the dominant tumor-suppressive factor (Supplementary Fig. 18a–d). Together, these findings indicate that NKX2-1 and likely other transcription factors mediate a functional link between LKB1 and C/EBPα in suppressing lung tumor growth and maintaining ATII differentiation.DiscussionAlthough tumor suppressor loss represents a major class of genetic alterations in cancer, the direct characterization of the function of these inactivated genes in vivo remains challenging. The advent of strategies to reversibly inactivate tumor suppressor function in vivo within mouse models has enabled the establishment of causal relationships between tumor suppressors and the physiological programs that they govern15. Here, we employed the XTR system to identify processes regulated by LKB1, which is among the most frequently altered tumor suppressors in human lung cancer and one of the most potent suppressors of oncogenic KRAS-driven lung tumor growth19,42,87. To complement recent targeted efforts that identified SIKs as potent tumor-suppressive effectors among the direct substrates of LKB1 kinase activity, we leveraged reversible inactivation to identify LKB1-driven processes in an unbiased fashion35,36.Previous studies on tumor suppressor function in vivo have illuminated diverse responses to tumor suppressor restoration in vivo. Trp53 restoration drives regression of malignant lung adenocarcinomas but has little effect in early adenomas88. In contrast, Rb1 restoration blocks lung tumor progression to more advanced grades, impairs metastatic progression, and transiently inhibits tumor growth18. Strikingly, Apc restoration in colorectal tumors drives complete regression and restoration of normal tissue function, even in the context of oncogenic KRAS and concomitant Trp53 inactivation20. Despite these examples, it remains plausible that the dependency on the absence of a tumor suppressor could diminish during tumor progression, thereby yielding established tumors that are insensitive to tumor suppressor reconstitution6. In fact, recent work has demonstrated that LKB1 rescue in a subset of human lung cancer cell lines is insufficient to revert stable epigenetic changes that stem from LKB1 loss29. However, in our experiments, Lkb1 restoration suppressed proliferation and stably blocked the growth of established early-stage tumors, even over relatively long periods following Lkb1 restoration (Figs. 1c–e and 2b–e and Supplementary Figs. 3a, b and 6b–d). Furthermore, this growth-suppressive effect was conserved in the allograft setting as well as in lung cancer cell lines in vitro (Supplementary Figs. 4 and 7).There may be more nuance to the response to Lkb1 restoration in vivo, including tumor stage or genotype specificity. Varying the timing of Lkb1 restoration throughout tumor development (including within metastases) and the generation of concomitant genetic alterations will be critical to extend the clinical applicability of future studies. For instance, p53 loss dampens the effect of Lkb1 restoration on early tumor growth, which could stem from accelerated tumor progression prior to Lkb1 restoration or implicate p53 as an effector involved in LKB1-driven growth suppression (Supplementary Fig. 5). Beyond permuting temporal and genetic variables, a greater understanding of the mechanisms by which LKB1 inactivation imparts epigenetic plasticity may aid in the distinction of subsets of LKB1-deficient lung cancers or neoplastic cell states therein that remain sensitive to LKB1 activity29.Lkb1 inactivation in oncogenic KRAS-driven lung tumors can lead to the emergence of diverse histological subtypes25,36. This expanded histological spectrum could stem from Lkb1 inactivation either enabling tumor outgrowth from distinct cells of origin or imparting plasticity to allow for the acquisition of alternative differentiation states59. Here, we demonstrate that the disruption of Lkb1 reduces C/EBP activity and enables the departure of neoplastic cells from ATII fate, thus potentially enhancing the propensity to assume alternative differentiation states (Fig. 6h). In addition to enabling the development of mucinous lung adenocarcinoma, LKB1 loss is associated with increased expression of markers of gastric differentiation, such as TFF1 and MUC5AC in human and mouse lung cancer34,36,43,52,89,90. Notably, the transition from ATII to gastric differentiation also results from the loss of NKX2-1 activity84,85. Like C/EBPα, NKX2-1 is critical for lung development and regulates ATII-associated processes like surfactant production, suggesting that LKB1 and C/EBPα may operate in concert with NKX2-1 to enforce ATII differentiation62,84,91,92,93,94,95,96. We demonstrate that NKX2-1 binds proximal to and is required for the expression of about half of the genes that are jointly dependent on LKB1 and C/EBPs. This is consistent with a model in which C/EBPs cooperate with NKX2-1 and other transcription factors downstream of LKB1 to promote the activation of genes involved in ATII differentiation (Fig. 6h). Thus, disruption of this program may facilitate the departure from a differentiated state and reversion to a progenitor-like state.The precise mechanism(s) by which LKB1 is linked to C/EBP transcriptional activity remains to be uncovered. C/EBPα appears to be the dominant tumor-suppressive paralog, with no evidence of functional redundancy (Supplementary Fig. 18c, d). This is consistent with the non-overlapping functions of C/EBP factors during development in addition to previous reports of a tumor-suppressive role for C/EBPα within the lung and a more general role in the inhibition of cell cycle progression63,97,98,99,100,101,102,103. Notably, CEBPA expression is frequently down-regulated in human non-small cell lung cancer due to promoter methylation or genetic deletion99,100,102. Within Lkb1-restored tumors, we noted a modest, yet significant, increase in Cebpa mRNA levels as compared to non-restored tumors, as well as a modest decrease in expression of the inhibitory paralog Cebpg, either of which could contribute to enhanced expression of C/EBPα targets (Supplementary Fig. 16a)82. SIK1/3 are key effectors of LKB1-mediated tumor suppression in lung cancer, and Sik-targeted tumors also exhibit lower expression of ATII markers relative to tumors driven by oncogenic KRAS alone, suggesting that SIKs may mediate the activation of the C/EBP-driven ATII differentiation program downstream of LKB1 (Fig. 6h and Supplementary Fig. 11g)35,36. Canonical targets of SIK activity are CRTC transcriptional coactivators and class IIa HDACs, both of which are inhibited by nuclear exclusion driven by SIK-mediated phosphorylation59. Notably, HDAC3 physically associates with NKX2-1, and both C/EBP and NKX2-1 motifs are enriched at HDAC3-bound sites in Lkb1-deficient lung cancer cells104. Thus, SIK-mediated regulation of HDAC trafficking could modulate the activity of C/EBPα and NKX2-1 targets via interference with corepressor complex recruitment104,105,106.Beyond the potential for a direct link between LKB1 signaling and activation of C/EBP target genes, the elevated expression of C/EBP targets and features of ATII differentiation within Lkb1-restored tumors could also be a product of indirect, selective or adaptive mechanisms. For instance, Lkb1 restoration could drive selection for lowly cycling cells that retain ATII features by promoting cell death among proliferative, less-differentiated cells. However, our analyses of markers of proliferation and cell death in both cell lines in vitro and tumors in vivo most strongly support a model in which Lkb1 restoration suppresses proliferation and drives reprogramming rather than promoting shifts in cell-state representation via selective induction of cell death (Fig. 2d–f and Supplementary Fig. 7). Alternatively, the induction of C/EBP targets and features of ATII differentiation could be an adaptive response independent of the LKB1-SIK axis of tumor suppression that facilitates the persistence of neoplastic cells when challenged by the reactivation of LKB1 signaling. Notably, AMPK has been shown to be required for endodermal fate specification during embryoid body formation, thus it is plausible that the enforcement of ATII differentiation could be attributed in part to the restoration of AMPK activity107. Future work centering on the elucidation of the pathways that govern C/EBP activity in lung epithelial cells will be critical to uncover a direct connection between LKB1 activity and the orchestration of ATII differentiation.Through the implementation of our Lkb1XTR allele, we have uncovered a role for LKB1 at the interface of differentiation enforcement and proliferative control in lung cancer in addition to demonstrating that established lung tumors remain sensitive to its tumor-suppressive activity. Beyond the context of lung tumors, we envision that the Lkb1XTR allele will enable the discovery of additional functions of LKB1 in other malignant and even normal contexts that would not have otherwise been identified through cell culture or in vivo systems involving constitutive inactivation of Lkb1. The ability to control LKB1 function in vivo should be particularly useful in assessing its role in broader physiological processes such as microenvironmental interactions and metabolic control. Overall, a deeper understanding of the direct functions of LKB1 in vivo will better inform how best to approach pharmacologically counteracting the molecular consequences of LKB1 loss in human cancer.MethodsEthics statementMice were maintained within Stanford University’s SIM1 Barrier Facility according to practices prescribed by the NIH and the Institutional Animal Care and Use Committee at Stanford University. Additional accreditation of Stanford University Research Animal Facility was provided by the Association for Assessment and Accreditation of Laboratory Animal Care. Protocols employed in this study were approved by the Administrative Panel on Laboratory Animal Care at Stanford University (Protocol #26696).Generation of Lkb1

XTR targeting vectorRight and left homology arms were amplified from the first intron of the Lkb1 locus and inserted at PacI-AatII and FseI-AscI sites of pNeoXTR f2 (Addgene #69159), respectively. Amplification of the Lkb1 right homology arm and addition of flanking 5’PacI and 3’AatII sites was performed using forward primer 5′-TTCTTAATTAAGGCGGGCGTTGCCAGGCGGGTGGC-3′ and reverse primer 5′-ACTGACGTCCTCTATAGACACTGGCCAAGTCTGAGGGAGTC-3’. Amplification of the Lkb1 left homology arm and the addition of flanking 5’ FseI and 3’ AscI sites as performed using forward primer 5′-ATAGGCGCGCCAGCTGCTCTTATTTTGCACAGGAAACGTG-3′ and reverse primer 5′-ATAGGCCGGCCAAAGAAGCCAGGCGCGACTTG-3’. The final targeting vector was then maxi-prepped and linearized with PmeI prior to purification by phenol/chloroform extraction.Generation of Lkb1

XTR alleleThe linearized targeting plasmid was electroporated into 129-derived ES cells using standard conditions. Neomycin-resistant colonies were picked, expanded, and screened for successful targeting by PCR (Left-Arm Junction: forward primer 5′-AGCACTTTTCCCACCTTTCC-3′ and reverse primer 5′-GGGGGAACTTCCTGACTAGG-3’; Right-Arm Junction: forward primer 5′-TGGCACAAAGCTTAGCCATA-3′ and reverse primer 5′-GCCTGGCTCATTTCTGTGTT-3’). Of 282 clones, one (0.35%) was successfully targeted. Blastocysts were injected with targeted ES cells, yielding four high-percentage male chimeras. A germline chimeric Lkb1XTR(neo)/+ male was crossed with Rosa26FLPe mice (The Jackson Laboratory: stock no. 003946) and the progeny were screened for NeoR deletion (forward primer 5′-CTACCCCATCTATCCCTGAGCGTCACC-3′ and reverse primer 5′-CGTTGGCCCGTGGGGACTCTTTATCG-3’) and retention of the intact Lkb1XTR allele (forward primer 5′-CCCTCTTTGGGCCAGGTC-3′ and reverse primer 5’-CCCCCTGAACCTGAAACATA -3’). Lkb1XTR/+; Rosa26FLPe/+ mice were crossed with wild-type 129 mice and their progeny were screened for loss of Rosa26FLPe, thereby isolating Lkb1XTR/+ mice for intercrossing to yield Lkb1XTR/XTR mice (The Jackson Laboratory: stock no. 034052)108. Lkb1TR/+ mice were generated by crossing Lkb1XTR/XTR mice to CMV-Cre mice (The Jackson Laboratory: stock no. 006054)41. Lkb1 wild-type and Lkb1XTR/+ mouse embryonic fibroblasts (MEFs) were isolated from embryos between E12.5 and E16.5 prior to transduction with either Adeno-Cre and/or Adeno-FLPo, which were obtained from the Gene Transfer Vector Core at the University of Iowa.Generation of lentiviral vectorsLenti-sgRNA/Cre vectors encoding individual sgRNAs were generated as previously described109. Lenti-sgRNA/Cre vectors encoding two or three tandem sgRNA cassettes were constructed as described previously36. Briefly, individual sgRNAs were cloned into plasmids encoding mU6, hU6, or bU6 promoters and unique constant regions (Addgene plasmids #85995, 85996, and 85997) by site-directed mutagenesis. The resulting U6-sgRNA cassettes were amplified and appended with flanking homology sequences to enable concatenation within the pLL3.3 Lenti-Cre backbone (previously linearized by PCR) by Gibson assembly. The final sgRNA sequences cloned into lentiviral vectors are listed in Supplementary Table 1. The primer sequences used for cloning sgRNAs and assembling multi-sgRNA vectors are listed in Supplementary Table 2. The Neo1, Neo2, Neo3, non-targeting (NT)1, NT2, Lkb1, Sik1, Sik3 sgRNA sequences have been previously described36,42,109.Lenti-sgRNA/Cre vectors were then diversified via the addition of sgID-BC cassettes as described previously to enable multiplexing110. In brief, unique sgID-BC inserts flanked by BamHI and BspEI sites were produced via PCR with Lenti-sgRNA/Cre as a template using unique forward primers encoding the sgID-BC region and a universal reverse primer. The sgID-BC amplicons were then digested with BamHI and BspEI and ligated into the Lenti-sgRNA/Cre backbones that had been previously linearized using BamHI and XmaI. The resultant colonies were then pooled for each vector prior to plasmid DNA extraction.To generate lentivirus, Lenti-sgRNA/Cre vectors were individually co-transfected into 293T cells using polyethylenimine along with pCMV-VSV-G (Addgene #8454) envelope and pCMV-dR8.2 dvpr (Addgene #8455) packaging plasmids. Viral supernatants were collected at 36 and 48 hours post-transfection, passed through a 0.45-µm filter (Millipore: SLHP033RB), and sedimented by ultracentrifugation (1.12 × 105 × g for 1.5 h at 4 °C), prior to resuspension in sterile PBS overnight at 4˚C. Each virus was titered against a lentiviral Cre stock of known titer using immortalized LSL-YFP MEFs (Dr. Alejandro Sweet-Cordero/UCSF). Each lentivirus was stored at −80 °C and later thawed and diluted or pooled at equal ratios for multiplexed experiments prior to use in vivo.Mice, tumor initiation, and treatmentKrasLSL-G12D (The Jackson Laboratory: stock no. 008179), p53flox (The Jackson Laboratory: stock no. 08462), H11LSL-Cas9 (The Jackson Laboratory: stock no. 027632), Rosa26FLPo-ERT2 (The Jackson Laboratory: stock no. 018906), and Rosa26LSL-tdTomato (ai9 and ai14 alleles; The Jackson Laboratory: stock no. 007909 & 007908) mice have been previously described109,111,112,113,114. All mice were on a C57BL/6J:129 mixed background except for NOD/SCID/γc (NSG; The Jackson Laboratory: stock no. 005557) mice used for transplantation experiments. The Rosa26LSL-tdTomato ai14 allele was implemented specifically with the Lkb1XTR mice, as the ai9 allele retains an additional FRT site within the PGK-NeoR cassette, which renders the tdTomato coding sequence susceptible to FLPo-ERT2-mediated deletion112. All mouse experiments included cohorts of mixed male and female mice aged 6 to 12 weeks (at tumor initiation) for autochthonous lung tumor models and 6 to 10 weeks for allograft models.Lung tumors were initiated via intratracheal delivery of 60 µL of lentiviral Cre diluted in sterile PBS115. For comparing lung tumor burden between Lkb1 wild-type and Lkb1XTR/XTR contexts, tumors were initiated in KT, KT; Lkb1XTR/XTR mice with 7.50 ×104 IFU Lenti-Cre. To assess the impact of long-term Lkb1 restoration on tumor burden, KT, KT; Lkb1XTR/XTR, and KT; Lkb1XTR/XTR; FLPo-ERT2 mice were transduced with 7.50 ×104 IFU Lenti-Cre. For survival analysis, lung tumors were initiated in KT, KT; Lkb1XTR/XTR, and KT; Lkb1XTR/XTR; FLPo-ERT2 mice with 2.50 ×105 IFU Lenti-Cre. To generate tumors for longitudinal µCT and 18F-FDG PET/CT imaging, KT; Lkb1XTR/XTR, and KT; Lkb1XTR/XTR; FLPo-ERT2 mice were transduced at 1.50 ×104 IFU/mouse. To assess the acute response to Lkb1 restoration at the histological, transcriptional (bulk and single-cell), and proteomic levels, tumors were initiated in KT; Lkb1XTR/XTR, and KT; Lkb1XTR/XTR; FLPo-ERT2 mice using 7.50 ×104 IFU Lenti-Cre. For bulk RNA-seq, Lkb1 wild-type tumors were generated via transduction of KT mice with 2.50 ×104 IFU/mouse. For both primary and secondary Tuba-seq screens, KT and KT;H11LSL-Cas9 mice were transduced with 2.50 ×105 and 1.00 ×105 IFU pooled Lenti-sgRNA/Cre, respectively. To validate tumor-suppressive capacity C/EBP transcription factors, tumors were initiated in KT and KT;H11LSL-Cas9 mice using 5.00 ×104 IFU of either Lenti-sgInert/Cre (sgNeo1/sgNT1/sgNeo2) or Lenti-sgCebps/Cre (sgCebpa/sgCebpb/sgCebpd). Finally, to generate tumors for comparing the gene expression profiles of C/ebp- and Lkb1-targeted tumors, KT;H11LSL-Cas9 mice were transduced with either Lenti-sgInert/Cre, Lenti-sgCebps/Cre, or Lenti-sgLkb1/Cre at 7.50 × 104 IFU/mouse.Mice were administered tamoxifen (Sigma-Aldrich: T5648) in doses of 4 mg as indicated for each experiment. In general, mice received single doses on 2 consecutive days, followed by weekly single doses for the duration of the experiment. Tamoxifen was dissolved in a mixture of 10% ethanol (Sigma-Aldrich: E7023) and 90% corn oil (Sigma-Aldrich: C8267) to a concentration of 20 mg/mL and delivered via oral gavage. For measurement of BrdU incorporation, mice were administered 50 mg/kg BrdU (BD Pharmingen: 557892) intraperitoneally at 24 h prior to tissue harvest. BrdU was resuspended in sterile PBS to a concentration of 10 mg/mL. Mice were housed at 22 °C ambient temperature with 40% humidity and a 12-h light/dark cycle. The Stanford Institute of Medicine Animal Care and Use Committee approved all animal studies and proceduresqRT-PCRTissues for assessing Lkb1 mRNA levels were flash-frozen immediately following harvest. While thawing in preparation for lysis, tissues were manually disrupted on dry ice using RNase-Free Disposable Pellet Pestles (Thermo Fisher Scientific:12-141-368). Tissues were repeatedly passed through a 20 G needle to yield a finer homogenate prior to the addition of RLT buffer containing 1% β-mercaptoethanol. RNA was extracted using Allprep DNA/RNA Mini Kit (Qiagen: 80204). cDNA was generated using the ProtoScript® First Strand cDNA Synthesis Kit (NEB: E6300). Measurements of Lkb1 and Gapdh expression levels were performed in triplicate using gene-specific primers (Lkb1 Fwd: 5’-CGAGGGATGTTGGAGTATGAG-3’; Lkb1 Rvs: 5’-AGCCAGAGGGTGTTTCTTC-3’; Gapdh Fwd: 5’-CAGCCTCGTCCCGTAGAC-3’; Gapdh Rvs: 5’-CATTGCTGACAATCTTGAGTGA-3’) and PowerUp™ SYBR™ Green Master Mix (Thermo Fisher Scientific: A25776) on an HT7900 Fast Real-Time PCR System with 384-Well Block Module (Applied Bioscience). Data were acquired using the Sequence Detection Systems Software v2.4.1 in Absolute Quantitation mode.Western blottingPellets of sorted neoplastic cells were stored at -80˚C and later lysed directly in NuPAGE™ LDS Sample Buffer (Thermo Fisher Scientific: NP0007) containing 5% β-mercaptoethanol (Sigma-Aldrich: M3148). Tissues for assessing LKB1 protein levels were flash-frozen immediately following harvest. While thawing in preparation for lysis, tissues were manually disrupted on dry ice using RNase-Free Disposable Pellet Pestles (Thermo Fisher Scientific:12-141-368). Tissues were repeatedly passed through a 20 G needle to yield a finer homogenate prior to the addition of RIPA buffer (Thermo Fisher Scientific: 89900) containing proteinase/phosphatase inhibitor cocktail (Thermo Fisher Scientific: 78442). For bulk tissue lysates, protein concentration was measured using BCA protein assay kit (Thermo Fisher Scientific: 23250). For sorted cells, a fixed number of cells was loaded into each well, whereas for bulk lysates, 25 µg of lysate was loaded into each well of 4-12% Bis-Tris gels (Thermo Fisher Scientific: NP0323). Electrophoresis was performed with MES buffer (Thermo Fisher Scientific: NP0002) and resolved lysates were subsequently transferred to polyvinyl difluoride (PVDF) membranes (BioRad: 162-0177) according to standard protocols. Membranes were blocked in 5% milk and subsequently probed with primary antibodies against LKB1 (Cell Signaling Technology: 13031; 1:1000 dilution) and GAPDH (Cell Signaling Technology: 5174; 1:10,000 dilution), as well as secondary HRP-conjugated anti-mouse (Santa Cruz Biotechnology: sc-2005) and anti-rabbit (Santa Cruz Biotechnology: sc-2004) antibodies. Blots were visualized using Supersignal® West Dura Extended Duration Chemiluminescent Substrate (Thermo Fisher Scientific: 37071) and exposed on blue autoradiography film (Morganville Scientific: FM0200).Histology and immunohistochemistryLung lobes were fixed in 4% formalin for 24 h, stored in 70% ethanol, and later paraffin embedded. Hematoxylin–eosin staining was performed using standard methods. Total tumor burden (tumor area/total area x 100%) and individual tumor sizes were calculated using ImageJ. Immunohistochemistry was performed on 4-µm sections using the Avidin/Biotin Blocking Kit (Vector Laboratories: SP-2001), Avidin-Biotin Complex kit (Vector Laboratories: PK-4001), and DAB Peroxidase Substrate Kit (Vector Laboratories: SK-4100) following standard protocols using the Sequenza system. The following primary antibodies were used: Cleaved Caspase 3 (Cell Signaling Technologies: 9661S; 1:100 dilution), phosphorylated Histone H3 Serine 10 (Cell Signaling Technologies: 9701S; 1:100 dilution), Ki-67 (BD Biosciences: 550609; 1:100 dilution), NKX2-1 (Abcam: ab76013; 1:200 dilution), and HMGA2 (Biocheck: 59170AP; 1:1000 dilution). For, Ki-67 staining, the mouse-on-mouse immunodetection kit (Vector Laboratories: BMK-2202) was used to block endogenous mouse IgG. IHC was performed using Avidin/Biotin Blocking Kit (Vector Laboratories: SP-2001), Avidin-Biotin Complex kit (Vector Laboratories: PK-4001), and DAB Peroxidase Substrate Kit (Vector Laboratories, SK-4100) following standard protocols. Sections were developed with DAB and counterstained with hematoxylin. The frequency of H3P- and Ki-67-positive nuclei were quantified using ImageJ on images of ×20 fields, and cleaved caspase 3-positive cells were quantified by direct counting on images of ×20 fields.Mouse cell linesCell lines were generated from primary tumors from KrasLSL−G12D;Trp53flox/flox (cell line 394T444), KrasLSL−G12D;Trp53flox/flox;Lkb1XTR/XTR;Rosa26LSL−tdTomato (cell line 3406) and KrasLSL−G12D;Trp53flox/flox;Lkb1XTR/XTR;Rosa26FlpOER/LSL−tdTomato (cell lines 2841T6, 3841T4, and 2804T5B) mice previously transduced with lentiviral Cre. To establish cell lines, individual tumors were micro-dissected from tumor-bearing lungs, minced, and directly cultured in DMEM (Thermo Fisher Scientific 11995081) supplemented with 10% FBS (Phoenix Scientific), 1% penicillin-streptomycin-glutamate (Thermo Fisher Scientific 10378016), and 0.1% amphotericin B (Thermo Fisher Scientific 15290018) at 37 °C and 5% CO2 until cell lines were established. Cells were authenticated for genotype. To induce Lkb1 restoration, cells were treated with either 1 μM 4-hydroxytamoxifen (4-OHT; Sigma Aldrich H7904) dissolved in 100% ethanol or vehicle (1:2000 100% ethanol). All cell lines included in this study tested negative for mycoplasma contamination (Lonza MycoAlert Mycoplasma Detection Kit, #LT07-218).Cell cycle and cell death assaysFor cell cycle and death analyses, 2.00 × 105 cells were seeded per well within 6-well plates in triplicate for each experimental group. Cells were treated with 4-OHT or ethanol for 48 h prior to re-plating at 1.00 × 105 cells per well. Culture media was changed at 72 h. At 96 h, the cells were 30–50% confluent, when the culture media containing detached dead cells were collected and later combined with trypsinized, detached cells. The attached cells were labeled with EdU for 45 min, washed, trypsinized, and counted. 1.00 × 105 cells were subjected to EdU-AF647 (Thermo Fisher Scientific C10424) and FxCycle Violet (Thermo Fisher Scientific F10347) double staining following the vendor’s protocols. Another 1.00 × 105 cells were stained with Annexin V (Thermo Fisher, A23204) and DAPI. 5.00 × 104 events were recorded on a BD LSRII flow cytometer, gated on forward/side scatter and singlets, and analyzed for cell cycle or death. Representative gating schemes for cell cycle and cell death analyses are included in Supplementary Fig. 19a, b.µCT and 18F-FDG PET/CT imagingSerial measurements of tumor size were captured by µCT using the Trifoil CT eXplore CT120 with respiratory gating. Using MicroView v.2.5.0 (Parallax Innovations), lung tumors were captured within advanced regions generated using the spline function and measures of tumor volume were acquired by determining the volume of voxels that fall within a defined range of pixel intensity that corresponds to each tumor mass. Measures of tumor size were reported in terms of size relative to the initial measurement of a given tumor. Mouse imaging was staggered on the basis of initial tumor detection and thus the relative timing of tumor measurements was variable. To align measurement intervals across all tumors in the study, interpolated values were used to aggregate tumors into cohorts, and measures of tumor size were reported in terms of weeks relative to treatment initiation. Non-interpolated measurements are shown in Supplementary Fig. 6b.18F-FDG-PET/CT imaging was performed as previously described116,117. 18F-FDG tracer was delivered by retro-orbital injection. 18F-FDG signal was measured in terms of maximum percent injected dose per gram (%ID/g) for each tumor. Measurements of 18F-FDG uptake were reported in terms of fold change relative to pre-treatment levels.Tumor dissociation and cell sortingMicro-dissected lung tumors were dissociated with collagenase IV, dispase, and trypsin at 37°C for 30 minutes as previously described118. The digestion buffer was then neutralized with cold L-15 media (Thermo Fisher Scientific: 21083027) containing 5% FBS (Gemini Bio) and DNaseI (Sigma-Aldrich: DN25). Dissociated cells were treated with ACK Lysis Buffer (Thermo Fisher Scientific: A1049201) and resuspended in PBS containing 2 mM EDTA (Promega: V4233), 2% FBS, and DNase I. For the isolation of neoplastic cells, dissociated cells were stained with DAPI and antibodies against CD45 (BioLegend: 103112; 1:800 dilution), CD31 (BioLegend: 102402; 1:800 dilution), F4/80 (BioLegend: 123116; 1:800 dilution), and Ter119 (BioLegend: 116212; 1:800 dilution) to exclude hematopoietic and endothelial cells. FACSAria™ sorters (BD Biosciences) were used for cell sorting. For sorting of total cells within tumors for single-cell RNA-seq, dissociated cells were stained with DAPI only to exclude dead cells. Representative gating scheme included in Supplementary Fig. 20a.Intratracheal transplant of neoplastic cellsFor the transplant of treatment-naïve neoplastic cells from KT; Lkb1XTR/XTR;FLPo-ERT2 donor mice, tumor-bearing lungs were extracted en bloc, dissociated into individual lobes, and maintained on ice. Individual tumor nodules were then extracted under a dissecting microscope, minced, and aggregated prior to enzymatic dissociation as described in the Tumor Dissociation and Cell Sorting section. Following red blood cell lysis and resuspension in PBS, a minor fraction of the resulting single-cell suspension was set aside for staining and flow cytometric analysis as described in the Tumor Dissociation and Cell Sorting section to determine the density of lineage-negative, tdTomatopositive cells. The remaining neoplastic cells suspended in PBS were administered to NSG recipient mice via intratracheal delivery. For the transplant of neoplastic cells derived from tamoxifen-treated KT;Lkb1XTR/XTR, and KT; Lkb1XTR/XTR;FLPo-ERT2 donor mice, the density of neoplastic cells within each donor suspension was first assessed by flow cytometry and then normalized such that each NSG recipient cohort received an equal number of neoplastic cells (5.00 × 104 cells/mouse).Bulk RNA-seq library preparationTotal RNA was prepared from sorted pellets of neoplastic cells ranging from 2.50 × 104 to 1.00 × 105 cells using the AllPrep DNA/RNA Micro Kit (Qiagen: 80284). RNA quality was assessed using the RNA6000 PicoAssay kit on the Agilent Bioanalyzer 2100, and samples with a RIN score below seven were excluded. Two to ten nanograms of total RNA served as input for the preparation of RNA-Seq libraries using the Trio RNA-Seq, Mouse rRNA kit (Tecan Genomics: 0507-32). Purified libraries were assessed using the Agilent High Sensitivity DNA kit (Agilent Technologies: 5067-4626) and then sequenced on an Illumina NextSeq 550 (2 × 75 bp High-Output).Analysis of bulk RNA-seq dataPaired-end bulk RNA-seq reads were aligned to the mm10 mouse genome using STAR (v2.6.1d) 2-pass mapping with standard parameters and an sjdbOverhang of 75 bp. Estimates of transcript abundance were obtained using RSEM (v1.2.30) using standard parameters119,120. The differentially expressed genes between different tumor genotypes were called by DESeq2 (v1.26.0) using transcript abundance estimates via tximport121,122. The DESeq2-calculated fold changes were used to generate ranked gene lists for input into GSEA (v3.0)123. GSEA results using the GO Biological Process module were imported into Cytoscape (v3.8.2) with the EnrichmentMap plugin for network construction using default parameters124,125. Networks were ported to R using ggraph (v2.0.4) and clusters of related GO terms were defined using the edge betweenness community detection algorithm in igraph (v1.2.6)126. K-means clusters were defined in ComplexHeatmap (v2.2.0) and GO term enrichment analysis was performed using compareCluster in ClusterProfiler (v3.14.3)127,128. For motif enrichment, the differentially expressed genes with absolute log2 fold changes >1 and a false discovery rate <0.05 were compiled into gene lists, converted to RefSeq identifiers using biomaRt, and used as input for Pscan (−450 to +50 bp from the TSS) using either the JASPAR 2018 non-redundant or TRANSFAC databases129.Analysis of previously published gene expression datasetsGene expression data derived from lung tumors in genetically engineered mice under accession numbers GSE6135, GSE21581, GSE69552, and GSE133714 were acquired from NCBI Gene Expression Omnibus using the GEOquery package25,52,53,130. Differential expression was computed using limma, and the resulting log2 fold changes were used to generate ranked gene lists for input into GSEA123,131. For the comparison of KrasG12D and KrasG12D;Nkx2-1Δ/Δ tumors by RNA-seq, log2 fold changes were directly downloaded from https://doi.org/10.7554/eLife.38579.01986.For the generation of signatures of alveolar type I and type II identities, single-cell gene expression data were acquired from the sources below54,66,67,68,69,70,71,72. Each dataset was loaded into Seurat and the FindMarkers function (only.pos = TRUE, min.pct = 0.25, logfc.threshold = 0.25) was performed on the basis of the curated cell type identities for each dataset. The cut-offs used for each dataset to establish gene sets are listed. Gene sets were then compiled into a GMT file using GSEABase (v1.48.0).Tabula Muris/Tabula Muris Senis67,71—processed Seurat objects obtained from https://www.synapse.org/#!Synapse:syn21560554Mouse Cell Atlas72—fetal and adult lung DGE matrices accessed at http://bis.zju.edu.cn/MCA/dpline.html?tissue=LungStrunz, et al.66—lung epithelial high-resolution Seurat object obtained from https://github.com/theislab/2019_StrunzLittle, et al.68—Cell Ranger outputs for control lung obtained from the Gene Expression Omnibus: GSE129584Angelidis, et al.69—Seurat object obtained from https://github.com/gtsitsiridis/lung_aging_atlasGuo, et al.70—DGE matrices derived from developing lungs obtained from the Gene Expression Omnibus: GSE122332Treutlein, et al.54—processed SingleCellExperiment file obtained courtesy of the Hemberg Lab at https://hemberg-lab.github.io/scRNA.seq.datasets/mouse/tissues/Mass spectrometryPellets of sorted neoplastic cells were stored at −80˚C and later resuspended in PBS prior to loading on a Whatman QM-A Quartz Microfiber Filter (GE Life Science: 1851-047) microreactor tip. Samples were then lysed, digested with trypsin/lys-c (Promega: V5073), and de-salted using C18 (Empore: 320907D) stage tips as described previously132. Eluted samples were dried and resuspended with Solution A (2% ACN, 0.1% FA) for mass spectrometry analysis.Samples were analyzed on the timsTOF Pro (Bruker Daltonics), an ion-mobility spectrometry quadrupole time of flight mass spectrometer. Specifically, a nanoElute (Bruker Daltonics) high-pressure nanoflow system was connected to the timsTOF Pro. Peptides were delivered to reversed-phase analytical columns (25 cm × 75 μm i.d., Ionopticks: AUR2-25075C18A-CSI). Liquid chromatography was performed at 40 °C, and peptides were separated on the analytical column using a 120 min gradient (solvent A: 2% ACN, 0.1% FA; solvent B: 0.1% FA, in ACN) at a flow rate of 400 nL/min. A linear gradient was applied for 60 min to 15%, 30 min to 23%, 10 min to 35%, followed by a step to 80% B in 10 min and held for 10 min for wash. The timsTOF Pro was operated in PASEF mode with the following settings: Mass Range 100 to 1700m/z, 1/K0 Start 0.60 V·s/cm2, End 1.6 V·s/cm2, Ramp time 100 ms, Lock Duty Cycle to 100%, Capillary Voltage 1600, Dry Gas 3 l/min, Dry Temp 180 °C, PASEF settings: 10 MS/MS, Scheduling Target intensity 500000, CID collision energy 10 eV.Bruker raw data files were analyzed by msfragger using the tool FragPipe133. Msfragger was run using the default modifications with an error tolerance of 20 ppm for precursors and + /− 40 ppm for fragments. We used a mouse protein database downloaded from RefSeq on 06/18/2018. Peptide and protein identifications were validated using PeptideProphet and quantitation was done using IonQuant with ‘match between runs’ and selecting the MaxLFQ method.Razor intensities were analyzed using the DEP package134. Briefly, contaminants and species detected in less than 25% of samples were filtered out. Intensities were normalized by variance stabilizing transformation and missing values were imputed using the MinProb imputation method. Differential expression was assessed using the limma package131. Fold changes calculated with limma were used to generate ranked gene lists for input into GSEA123. GSEA results using the GO Biological Process module were imported into Cytoscape with the EnrichmentMap plugin for network construction using default parameters124,125. Networks were ported to R using ggraph and clusters of related GO terms were defined using the edge betweenness community detection algorithm in the igraph package126.Single-cell RNA-seq library preparationSorted cells were pelleted at 300 × g for 5 min to resuspend in PBS. Cell density was then assessed on a hemacytometer and adjusted to the target density. Cells were loaded in each channel of Chromium Chip B (10X Genomics: 1000074) with a recovery target of 8,000 cells per sample, and emulsions were generated on the Chromium Controller (10X Genomics). Libraries were constructed using the Chromium Single Cell 3′ Library & Gel Bead Kit v3 kit (10× Genomics: 1000075). 10× libraries derived from total cells were sequenced on Illumina NextSeq 500 and Hi-Seq 2500 platforms (26 bases for Read 1, 8 bases for i7 Index 1, and 91 bases for Read 2), whereas sorted neoplastic cell libraries were sequenced on an Illumina Nova-seq 6000 (26 bases for Read 1, 8 bases for i7 Index 1, and 90 bases for Read 2).Analysis of single-cell RNA-seq dataReads were aligned to the mm10 genome and feature counts were obtained using Cell Ranger (v3.0.2) (10× Genomics). Feature-barcode matrices were then imported into R using Seurat (v3.2.0) (minimum of 500 features/cell for sorted neoplastic dataset and 200 features/cell for the total cell dataset) and merged into Seurat objects for pre-processing, normalization (regressing out nCount_RNA in ScaleData), dimensional reduction (2000 variable features for each dataset, 6 and 25 dimensions were used for sorted neoplastic and total cell datasets, respectively), and clustering (resolutions of 0.3 and 0.1 were passed to FindClusters to implement the Louvain algorithm for community detection within sorted neoplastic and total cell datasets, respectively)135. Cells were filtered on the basis of percent mitochondrial reads and maximum feature count using percentile-based cutoffs. For the sorted neoplastic cell dataset, putative stromal cells (Pecam1+, Cdh5+, Ramp2+ endothelial cells and Col1a1+, Col1a2+, Col3a1+, Mgp+ fibroblasts) were filtered out following preliminary clustering analysis. For the total cell dataset, tdTomatopositive cells outside of the epithelial compartment were excluded from downstream analyses. For cell-type prediction within the total cell dataset, SingleR (v1.4.1) was used with the Tabula Muris lung dataset as a reference (following conversion of Seurat object to SingleCellExperiment and transformation with logNormCounts in scater)71,136,137. For the total cell dataset, Louvain-based clusters were collapsed into pseudobulk samples and differential expression analysis between restored and non-restored samples was performed using muscat (v1.4.0)138.Trajectory inference analysis was performed using Monocle3 (v0.2.1) with standard parameters (following conversion to CellDataSet; close_loop set to FALSE in learn_graph; ATII-like subpopulations was manually defined as the root population)139. For RNA velocity analysis, spliced, unspliced, and ambiguous matrices were generated using the run10x command in velocyto (v0.17.17) with default parameters140. The resulting loom files were imported into Seurat with the ReadVelocity command in SeuratDisk, integrated with meta data, subsetted to only those cells that passed QC before, and exported to h5ad format. RNA velocity analysis was then performed using scvelo (v.0.2.3) with standard parameters141.Isolation of genomic DNA from mouse lungs and preparation of Tuba-seq librariesGenomic DNA was isolated from bulk tumor-bearing lung from each mouse following the addition of three spike-in controls (5.00 × 105 cells per control) to enable absolute quantification of cell number using Tuba-seq as described previously110. Libraries were prepared by single-step amplification of the sgID-BC region from a total of 32 µg of genomic DNA per mouse across eight 100-µL reactions using NEBNext Ultra II Q5 Master Mix (New England Biolabs: M0544L). To enable computational removal of chimeric reads that result from index hopping during ultra-deep sequencing, the sgID-BCs were amplified using defined dual-indexing primer pairs with unique i5 and i7 indices. The unique dual-indexed primers used were forward: AATGATACGGCGACCACCGAGATCTACAC- 8-nucleotide i5 index -ACACTCTTTCCCTACACGACGCTCTTCCGATCT-6N to 9 N (random nucleotides to increase diversity)-GCGCACGTCTGCCGCGCTG and reverse: CAAGCAGAAGACGGCATACGAGAT- 6-nucleotide i7 index -GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT-6N to 9N (random nucleotides to increase diversity) -CAGGTTCTTGCGAACCTCAT. The PCR products were subjected to double-sided purification using Agencourt AMPure XP beads (Beckman Coulter: A63881). Purified libraries were assessed using the Agilent High Sensitivity DNA kit (Agilent Technologies: 5067-4626) on the Agilent 2100 Bioanalyzer (Agilent Technologies: G2939BA). Individual libraries were pooled in a weighted format on the basis of total lung weight, and the final pool was cleaned up using a single-sided purification with Agencourt AMPure XP beads. Libraries were sequenced on Illumina® HiSeq 2500 and NextSeq 500 platforms to obtain 150-bp paired-end reads.Tumor barcode sequencing analysisOnly those reads containing complete sgID-BC cassettes (8-nucleotide sgID region and 30-nucleotide barcode: GCNNNNNTANNNNNGCNNNNNTANNNNNGC) were retained. Each sgID corresponds to a unique Lenti-sgRNA/Cre vector included in the lentiviral pool, whereas the 20N random nucleotide basis serves as a unique clonal identifier for each tumor. sgIDs were designed with a minimum hamming distance of three nucleotides. Read pairs exhibiting mismatches within this sgID-BC region were discarded to minimize the impact of sequencing error. Furthermore, we required perfect matching between sgIDs in forward reads with the known sgIDs that were included within each pool. Reads were then aggregated on the basis of the random barcode region to create unique barcode pileups that represent individual tumors. Tumors with random barcodes containing indels were discarded to avoid potential alignment errors and miscalculation of distances between barcodes. Any tumor with a barcode within a hamming distance of two nucleotides from a larger tumor was considered spurious and excluded to minimize the impact of PCR and sequencing errors. Measures of absolute cell number for each tumor were then calculated by multiplying the read counts for each barcode pileup (tumor) by the size of the spike-in controls (1.00 × 105 cells) and subsequently dividing by the average number of reads within each mouse for the three barcodes corresponding to the three spike-in controls that were added in during tissue processing. For the primary Tuba-seq screen, the median sequencing depth was ~1 read per 15 cells, and the minimum sequencing depth is ~1 read per 170 cells. For the secondary, C/ebp-targeted Tuba-seq screen, the median sequencing depth was ~1 read per 8 cells, and the minimum sequencing depth is ~1 read per 17 cells. The impact of GC amplification bias on tumor size was accounted for as described previously42. Tumor size cut-offs of 50 and 100 cells were applied for the primary and secondary Tuba-seq screens, respectively.Multiple metrics of tumor size distribution were examined, including various percentiles as well as the maximum-likelihood estimate of the mean assuming a log-normal distribution of tumor size42. Confidence intervals and p values were calculated by a nested bootstrap resampling approach to account for variation in sizes of tumors of a given genotype both across and within mice. First, the tumors of each mouse were grouped, and these groups (mice) were resampled. Second, all tumors of a given mouse resampling were bootstrapped on an individual basis (500 repetitions). False discovery rates were calculated using the Benjamini-Hochberg procedure.Analysis of previously published NKX2-1 ChIP-seq dataBedGraph files under accession GSM1059354 corresponding to NKX2-1 ChIP-seq performed on oncogenic KRAS-driven lung tumors were acquired from NCBI Gene Expression Omnibus85. De novo motif enrichment at NKX2-1 bound sites was performed using HOMER findmotifs.pl using default parameters142. Gene associations to NKX2-1-bound sites were generated using GREAT analysis using mm9 assembly and a window of −2 to +1 kb relative to TSS143.Reporting summaryFurther information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

Next-generation sequencing data for the Tuba-Seq and RNA-Seq (bulk and single-cell) experiments are accessioned under the GSE179560 SuperSeries at NCBI Gene Expression Omnibus. Shotgun proteomics data are accessioned under PXD026738 at PRIDE. Lenti-sgRNA/Cre plasmids generated in this study are available through the Winslow Lab plasmid collection on Addgene [https://www.addgene.org/Monte_Winslow/]. Lkb1XTR/XTR mice generated in this paper are available at The Jackson Laboratory (Stock no. 034052). Lkb1XTR/XTR mouse lung cancer cell lines are available from the corresponding author upon request. JASPAR 2018 non-redundant [https://jaspar.genereg.net/api/v1/live-api/] and TRANSFAC [http://cisbp.ccbr.utoronto.ca/index.php] databases are publicly available and accessible via Pscan [http://159.149.160.88/pscan/]. Previously published gene expression data derived from lung tumors in genetically engineered mice are available under accession numbers GSE6135, GSE21581, GSE69552, and GSE133714 at NCBI Gene Expression Omnibus. Lung cell identity gene expression signatures were derived from publicly available single-cell RNA-seq datasets, including Tabula Muris & Tabula Muris Senis [https://www.synapse.org/#!Synapse:syn21560554]; Mouse Cell Atlas [http://bis.zju.edu.cn/MCA/dpline.html?tissue=Lung]; Strunz et al.66 [https://github.com/theislab/2019_Strunz]; Little et al.68—Gene Expression Omnibus: GSE129584; Angelidis et al.69 [https://github.com/gtsitsiridis/lung_aging_atlas]; Guo et al.70—Gene Expression Omnibus: GSE122332; Treutlein, et al.54 [https://hemberg-lab.github.io/scRNA.seq.datasets/mouse/tissues/]. Source data are provided with this paper.

Code availability

All custom codes used in this work are available from the corresponding author upon request. Scripts for analyzing the Tuba-seq datasets are available at https://github.com/lichuan199010/Tuba-seq-analysis-and-summary-statistics.

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Download referencesAcknowledgementsWe thank the Stanford Shared FACS facility, the Stanford Center for Innovation in in vivo Imaging, the Stanford Functional Genomics Facility, the Stanford Transgenic, Knockout and Tumor Model Center, and Stanford Animal Histology Services for technical support; A. Orantes for administrative support; L. Penland, N. Neff, N. Hughes, and L. Cong for support with single-cell RNA-seq; M. Yousefi and R. Tang for help with FACS; L. Andrejka for help with generating Tuba-seq libraries. C. Li, E. Shuldiner, and D. Petrov for support with Tuba-seq analysis; E. Snyder, J. Lipsick, and members of the Winslow laboratory for helpful comments. C.W.M. was supported by the NSF Graduate Research Fellowship Program and an Anne T. and Robert M. Bass Stanford Graduate Fellowship. J.J.B. was supported by NIH F32-CA189659. S.E.P. was supported by an NSF Graduate Research Fellowship Award and the Tobacco-Related Diseases Research Program Predoctoral Fellowship Award. H.C. was supported by a Tobacco-Related Disease Research Program (TRDRP) Postdoctoral Fellowship (28FT-0019). R.C. was supported by NIH 5T32GM007276. D.B.S. was supported by NIH R01-CA208642, DOD LCRP W81XWH-18-1-0295, and funding from the Jonsson Comprehensive Cancer Center. This work was supported by NIH R01-CA175336 (to M.M.W.), NIH R01-CA207133 (to M.M.W.), and NIH R01-CA230919 (to M.M.W.). This work was supported by a National Cancer Institute Cancer Center Support Grant (P30CA124435). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NCI.Author informationAuthors and AffiliationsCancer Biology Program, Stanford University School of Medicine, Stanford, CA, USAChristopher W. Murray, Min K. Tsai, Sarah E. Pierce, Peter K. Jackson & Monte M. WinslowDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USAJennifer J. Brady, Hongchen Cai & Monte M. WinslowDivision of Pulmonary and Critical Care Medicine, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USAMingqi Han & David B. ShackelfordJonsson Comprehensive Cancer Center, David Geffen School of Medicine, University of California, Los Angeles, CA, USAMingqi Han & David B. ShackelfordBaxter Laboratory, Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, CA, 94305, USARan Cheng, Janos Demeter & Peter K. JacksonDepartment of Biology, Stanford University, Stanford, CA, 94305, USARan ChengDepartment of Cancer Biology, University of Pennsylvania, Philadelphia, PA, 19104-6160, USADavid M. FeldserAbramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, PA, 19104-6160, USADavid M. FeldserDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USAPeter K. Jackson & Monte M. WinslowStanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USAPeter K. Jackson & Monte M. WinslowAuthorsChristopher W. MurrayView author publicationsYou can also search for this author in

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PubMed Google ScholarContributionsJ.J.B. designed and generated the Lkb1XTR allele under the supervision of D.M.F. and M.M.W. C.W.M. performed tumor burden experiments, survival analysis, µCT imaging, RNA-seq, and Tuba-seq experiments under the supervision of M.M.W. C.W.M. and M.K.T. performed immunohistochemistry. S.E.P. and M.K.T. performed qRT-PCR and western blot analysis. H.C. and S.E.P. sorted neoplastic cells. H.C. performed in vitro analysis of cell cycle and cell death. M.H. performed 18F-FDG PET/CT imaging under the supervision of D.B.S. R.C. and J.D. acquired and processed the mass spectrometry data under the supervision of P.K.J. C.W.M. and M.M.W. wrote the manuscript with contributions from all authors.Corresponding authorCorrespondence to

Monte M. Winslow.Ethics declarations

Competing interests

M.M.W. is a founder of, and holds equity in, D2G Oncology, Inc. The authors declare no other competing interests.

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Reprints and permissionsAbout this articleCite this articleMurray, C.W., Brady, J.J., Han, M. et al. LKB1 drives stasis and C/EBP-mediated reprogramming to an alveolar type II fate in lung cancer.

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LKB1 inactivation modulates chromatin accessibility to drive metastatic progression | Nature Cell Biology

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Article

Published: 02 August 2021

LKB1 inactivation modulates chromatin accessibility to drive metastatic progression

Sarah E. Pierce

ORCID: orcid.org/0000-0002-9145-95591 na1, Jeffrey M. Granja1,2 na1, M. Ryan Corces2, Jennifer J. Brady1, Min K. Tsai

ORCID: orcid.org/0000-0003-4732-42591, Aubrey B. Pierce1, Rui Tang1, Pauline Chu3, David M. Feldser

ORCID: orcid.org/0000-0001-5975-864X4, Howard Y. Chang

ORCID: orcid.org/0000-0002-9459-43931,2,5, Michael C. Bassik

ORCID: orcid.org/0000-0001-5185-84271,6, William J. Greenleaf

ORCID: orcid.org/0000-0003-1409-30951,2 & …Monte M. Winslow

ORCID: orcid.org/0000-0002-5730-95731,6,7 Show authors

Nature Cell Biology

volume 23, pages 915–924 (2021)Cite this article

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Cancer epigeneticsFunctional genomicsLung cancerMetastasis

AbstractMetastasis is the leading cause of cancer-related deaths and enables cancer cells to compromise organ function by expanding in secondary sites. Since primary tumours and metastases often share the same constellation of driver mutations, the mechanisms that drive their distinct phenotypes are unclear. Here we show that inactivation of the frequently mutated tumour suppressor gene LKB1 (encoding liver kinase B1) has evolving effects throughout the progression of lung cancer, which leads to the differential epigenetic re-programming of early-stage primary tumours compared with late-stage metastases. By integrating genome-scale CRISPR–Cas9 screening with bulk and single-cell multi-omic analyses, we unexpectedly identify LKB1 as a master regulator of chromatin accessibility in lung adenocarcinoma primary tumours. Using an in vivo model of metastatic progression, we further show that loss of LKB1 activates the early endoderm transcription factor SOX17 in metastases and a metastatic-like sub-population of cancer cells within primary tumours. The expression of SOX17 is necessary and sufficient to drive a second wave of epigenetic changes in LKB1-deficient cells that enhances metastatic ability. Overall, our study demonstrates how the downstream effects of an individual driver mutation can change throughout cancer development, with implications for stage-specific therapeutic resistance mechanisms and the gene regulatory underpinnings of metastatic evolution.

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Fig. 1: An LKB1–SIK axis regulates chromatin accessibility in lung adenocarcinoma.Fig. 2: LKB1 mutation status distinguishes the two main chromatin sub-types of human lung adenocarcinoma.Fig. 3: Genotype-specific activation of SOX17 expression in metastatic, LKB1-deficient cells.Fig. 4: LKB1-deficient primary tumours contain sub-populations of SOX17+ cells.Fig. 5: SOX17 regulates the chromatin accessibility state of metastatic, LKB1-deficient cells.Fig. 6: SOX17 regulates the metastatic ability of LKB1-deficient cells.

Data availability

RNA-seq, scATAC–seq and ATAC–seq data that support the findings of this study have been deposited in the Gene Expression Omnibus (GEO) under accession code GSE167381. The human lung adenocarcinoma data were derived from the TCGA Research Network (http://cancergenome.nih.gov/). The dataset derived from this resource that supports the findings of this study is publicly available at https://gdc.cancer.gov/about-data/publications/ATACseq-AWG. All other data supporting the findings of this study are available from the corresponding authors on request. Transcription factor binding motifs were derived from CIS-BP (http://cisbp.ccbr.utoronto.ca/index.php). Source data are provided with this paper.

Code availability

All custom code used in this work is available from the corresponding authors upon request. We also host a Github website that includes the main analysis code used in this study (https://github.com/GreenleafLab/LKB1_2021)44.

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Granja, J. M. GreenleafLab/LKB1_2021: Release_1.0.1 Zenodo https://doi.org/10.5281/zenodo.5035694 (2021).Download referencesAcknowledgementsWe thank J. Sage, A. Trevino and members of the Greenleaf and Winslow laboratories for comments. We thank the Stanford Shared FACS facility and the Veterinary Service Center for technical support. We thank A. Orantes for administrative support. S.E.P was supported by an NSF Graduate Research Fellowship Award and the Tobacco-Related Diseases Research Program Predoctoral Fellowship Award (grant number T31DT1900). This work was supported by National Institutes of Health (NIH) grant numbers R01-CA204620 and R01-CA230919 (to M.M.W.), RM1-HG007735 and UM1-HG009442 (to H.Y.C. and W.J.G.), R35-CA209919 (to H.Y.C.), UM1-HG009436 and U19-AI057266 (to W.J.G.), and in part by the Stanford Cancer Institute support grant (NIH grant P30-CA124435).Author informationAuthor notesThese authors contributed equally: Sarah E. Pierce, Jeffrey M. Granja.Authors and AffiliationsDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USASarah E. Pierce, Jeffrey M. Granja, Jennifer J. Brady, Min K. Tsai, Aubrey B. Pierce, Rui Tang, Howard Y. Chang, Michael C. Bassik, William J. Greenleaf & Monte M. WinslowCenter for Personal and Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USAJeffrey M. Granja, M. Ryan Corces, Howard Y. Chang & William J. GreenleafDepartment of Comparative Medicine, Stanford University School of Medicine, Stanford, CA, USAPauline ChuDepartment of Cancer Biology and Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USADavid M. FeldserHHMI, Stanford University School of Medicine, Stanford, CA, USAHoward Y. ChangChemistry, Engineering, and Medicine for Human Health (ChEM-H), Stanford University, Stanford, CA, USAMichael C. Bassik & Monte M. WinslowDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USAMonte M. WinslowAuthorsSarah E. PierceView author publicationsYou can also search for this author in

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PubMed Google ScholarContributionsS.E.P., J.M.G., M.M.W. and W.J.G. conceived the project and designed the experiments. S.E.P. led the experimental data production together with contributions from J.M.G., M.R.C., J.J.B., M.K.T., A.B.P., R.T. and P.C. S.E.P. and J.M.G. led the data analysis. S.E.P. performed the CRISPR screen analysis and RNA-seq analysis. J.M.G. and S.E.P. performed the ATAC–seq and scATAC–seq analysis. J.M.G. was supervised by H.Y.C and W.J.G. S.E.P. was supervised by M.C.B., W.J.G. and M.M.W. S.E.P., J.M.G., W.J.G. and M.M.W. wrote the manuscript with input from all authors.Corresponding authorsCorrespondence to

Sarah E. Pierce, William J. Greenleaf or Monte M. Winslow.Ethics declarations

Competing interests

W.J.G. and H.Y.C. are consultants for 10x Genomics, which has licensed IP associated with ATAC–seq. W.J.G. has additional affiliations with Guardant Health (consultant) and Protillion Biosciences (co-founder and consultant). M.M.W. is a co-founder of, and holds equity in, D2G Oncology, Inc. H.Y.C. is a co-founder of Accent Therapeutics, Boundless Bio, and a consultant for Arsenal Biosciences and Spring Discovery. The remaining authors declare no competing interests.

Additional informationPeer review Information Nature Cell Biology thanks Kwon-Sik Park, Tomi Makela and Skirmantas Kriaucionis for their contribution to the peer review of this work.Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Extended dataExtended Data Fig. 1 Validation and quality control of inducible LKB1 restoration model and genome-scale CRISPR/Cas9 screen.a. Schematic of restorable Lkb1TR/TR alleles. SA = splice acceptor, SD = splice donor, FRT = flippase recognition target. b. Schematic of the derivation of LKB1-restorable cell lines. c. Expression of LKB1 by immunoblot over a time-course of 4-OHT treatment, represented in hours (h) and days (d). HSP90 is a sample processing control. 25% and 10% of input after six days of 4-OHT treatment is shown for a visual comparison. d. Expression of LKB1 by immunoblot in LR1 and LR2 cells treated with vehicle or 4-OHT compared to a KPT cell line and a KPT;Lkb1−/− cell line. HSP90 is a sample processing control. e. RNA-sequencing reads mapping to the Lkb1 locus following six days of 4-OHT or vehicle treatment. f. Subcutaneous growth assay following injection of cell lines into recipient NSG mice. Tamoxifen or vehicle treatment was initiated on day 0. Mean tumor volume as measured by calipers of six tumors per condition +/− SEM is shown. g. Intravenous (i.v.) transplant assays. Left: Representative lung histology. Right: Change in % tumor area in LKB1-restored cells. Mean area of four mice per condition +/− SEM is shown. **p = 0.001, ***p = 0.0001, n.s. = not significant with a two-sided t-test. Scale bars represent 5 mm. h. Cumulative population doublings recorded over 12 days of 4-OHT treatment. Each cell line and condition was cultured and analyzed in triplicate. Mean +/− SEM is shown. **p = 0.0002 for LR1, **p = 0.0001 for LR2. i. Left: Representative image of clonogenic growth in LR1 cells. Right: % normalized area of cell growth. Each treatment group was cultured and analyzed in triplicate. Mean +/− SEM is shown. *p < 0.01, **p < 0.001, n.s. = not significant with a two-sided t-test. Scale bars represent 10 mm. p = 0.0001 for LR1 and p = 0.0059 for LR2. j. Heatmap of Pearson correlation matrix of log-normalized counts across all samples in the genome-scale CRISPR/Cas9 screen. k. Log2 fold enrichment of negative control sgRNAs and sgRNAs targeting Lkb1 at day 12 versus day 0.Source dataExtended Data Fig. 2 LKB1 restoration drives widespread changes in chromatin accessibility in lung adenocarcinoma cells.a. Schematic of preparing LKB1-deficient and LKB1-restored samples prior to ATAC-seq library preparation. Cell lines were treated with 4-OHT or vehicle for six days. b. Representative plot of aggregate signal around the transcription start site (TSS) for all ATAC-seq peaks in one vehicle-treated, LR1 replicate. This plot represents the signal-to-noise quantification of our ATAC-seq data. TSS enrichment scores greater than 10 indicate high quality ATAC-seq data. c. TSS enrichment scores for 16 ATAC-seq libraries with technical replicates. d. Differential accessibility across 178,783 ATAC-seq peaks following 4-OHT treatment in the LKB1-restorable (LR1 and LR2) and LKB1-unrestorable (LU1 and LU2) cell lines. The x-axis represents the log2 mean accessibility per peak and the y-axis represents the log2 fold change in accessibility following 4-OHT treatment. Colored points are significant (|log2 fold change | >0.5, FDR < 0.05). e. Percentage of differential peaks (|log2 fold change | >0.5, FDR < 0.05) across multiple ATAC-seq comparisons. f. Schematic of preparing samples for LKB1-restoration time-course. Cell lines were treated with 4-OHT for eight different time-points (0 hours, 6 hours, 12 hours, 24 hours, 36 hours, 48 hours, 4 days, and 6 days) in two cell lines (LR1 and LR2). g. and h. PCA (g) and k-means clustering (h) of 9,480 correlated, variable ATAC-seq peaks across the LKB1 restoration time-course in two cell lines (LR1 and LR2). Each row of the heatmap represents a z-score of log2 normalized accessibility across all samples within each cell line. i and j. SOX (i) and TEAD (j) motif accessibility changes (∆chromVAR deviation scores) across time in two cell lines (LR1 and LR2) treated with 4-OHT for the indicated time-points. Shaded area represents 95th percent confidence interval.Extended Data Fig. 3 Inactivating chromatin modifiers only delays LKB1-induced chromatin changes.a. Schematic of generating single knock-out populations of chromatin modifiers identified in the CRISPR screen, treating with 4-OHT or vehicle for six days, and processing for ATAC-seq. b. Principle component analysis (PCA) of the top 10,000 variable ATAC-seq peaks across the indicated LR1;Cas9 knock-out populations treated with 4-OHT or vehicle. c. K-means clustered heatmap of differential peak accessibility (log2 fold change) for each genotype of LR1;Cas9 cells treated with 4-OHT for up to 48 hours compared to 0 hours. All peaks differential between sgSafe (0 hours 4-OHT) and sgSafe (48 hours 4-OHT) are shown. Each row represents the log2 fold change of each genotype and time-point versus the same genotype’s initial time-point (day 0). d. Log2 fold change in mean peak accessibility for all peaks in k-means cluster 3 (top) and cluster 4 (bottom) from (c) for the indicated genotype and 4-OHT time-points compared to 0 hours 4-OHT. N = 2 technical replicates per sgRNA population and time-point. Box-whisker plot; lower whisker is the lowest value greater than the 25% quantile minus 1.5 times the interquartile range (IQR), the lower hinge is the 25% quantile, the middle is the median, the upper hinge is the 75% quantile and the upper whisker is the largest value less than the 75% quantile plus 1.5 times the IQR.Extended Data Fig. 4 SIK family members mediate LKB1-induced chromatin changes.a. Schematic of generating single and multiple sgRNA knock-out cell lines and processing for ATAC-seq. LR1;Cas9 cells were treated with 4-OHT or vehicle for six days. b. Left: Heatmap of peak accessibility between each knock-out population treated with 4-OHT or vehicle. Each row represents a z-score of log2 normalized accessibility across all samples. Right: Transcription factor hypergeometric motif enrichment in each k-means cluster. c. Percent of differential ATAC-seq peaks (|log2 fold change | >0.5, FDR < 0.05) across LKB1-restorable cells treated with 4-OHT or vehicle. d. SOX (top) and FOXA (bottom) motif accessibility changes (∆chromVAR deviation scores normalized to vehicle-treated sgSafe) across LKB1-restorable knock-out populations treated with 4-OHT or vehicle. e. Heatmap of Pearson correlation matrix of log2-normalized accessibility (in counts per million (CPM)) across LKB1 downstream effector knock-out genotypes with and without LKB1 restoration in LR1;Cas9 cells. f. PCA of the top 10,000 variable ATAC-seq peaks across LR1;Cas9 knock-out populations treated with 4-OHT or vehicle. Principle components besides PC1 (70.6%) account for <4% of the variance in the dataset. N = 2 technical replicates per sgRNA population. g. SOX (top) and FOXA (bottom) motif accessibility changes (∆chromVAR deviation scores normalized to vehicle-treated sgSafe) across LKB1-restorable knock-out populations treated with 4-OHT or vehicle. Line represents average between two technical replicates. h. Heatmap of Pearson correlation matrix of log2-normalized accessibility (in counts per million (CPM)) across LKB1 downstream effector knock-out genotypes with and without LKB1 restoration in LR1;Cas9 cells. i and j. PCA of the top 10,000 variable ATAC-seq peaks across LR1;Cas9 knock-out populations treated with 4-OHT or vehicle. Principle components besides PC1 account for <4% of the variance in the dataset. N = 2 technical replicates per sgRNA population.Extended Data Fig. 5 Loss of LKB1 partitions human lung adenocarcinoma primary tumors into two chromatin accessibility sub-types.a. Enrichment of mutations in Chromatin Type 2 tumors compared to Chromatin Type 1 tumors. Genes are ranked according to -log10(FDR), with Rank 1 (LKB1) being the most significant (see Methods), as indicated on the y-axis. Points are colored by the number of mutations in the TCGA-LUAD ATAC-seq dataset (out of 21 samples). b. ChromVAR deviation scores for the indicated transcription factor motifs for samples in the TCGA-LUAD ATAC-seq dataset. *p < 0.1, **p < 0.005, ****p < 10−6 using a two-sided t-test. p = 1×10−7 for RUNX, p = 0.002 for FOXA, and p = 1×10−7. N = 13 biologically independent samples for Chromatin Type 1 and 8 biologically independent samples for Chromatin Type 2. Box-whisker plot; lower whisker is the lowest value greater than the 25% quantile minus 1.5 times the interquartile range (IQR), the lower hinge is the 25% quantile, the middle is the median, the upper hinge is the 75% quantile and the upper whisker is the largest value less than the 75% quantile plus 1.5 times the IQR.Extended Data Fig. 6 Loss of LKB1 drives a unique chromatin accessibility state in human lung adenocarcinoma cell lines.a. Hierarchical clustering of human lung cancer cell lines using the Euclidian distance within the first three principle components from Fig. 2d. b. ChromVAR deviation scores for the indicated transcription factor motifs in eight human lung cancer cell lines at baseline. *p < 0.1, **p < 0.005, ****p < 10-6 using a two-sided t-test. p = 0.066 for FOXA, p = 0.003 for SOX, p = 3.1 ×10−7 for NR4A, and p = 0.001 for RUNX. N = 4 biologically independent samples for each group. Box-whisker plot; lower whisker is the lowest value greater than the 25% quantile minus 1.5 times the interquartile range (IQR), the lower hinge is the 25% quantile, the middle is the median, the upper hinge is the 75% quantile and the upper whisker is the largest value less than the 75% quantile plus 1.5 times the IQR. c. Comparison of the changes in motif accessibility (∆ chromVAR deviation scores) across LKB1-wild-type and LKB1-mutant human lung cancer cell lines (y-axis) and Chromatin Type 1 and Type 2 tumors (x-axis). Dark grey or colored points are called significantly different (q < 0.05) across both comparisons. Light grey points are not significant. A selection of motif families and their associated motif logos are indicated. d. Differential accessibility across ATAC-seq peaks following LKB1 wild-type expression in eight human lung cancer cell lines. The x-axis represents the log2 fold change in accessibility following LKB1 restoration. LKB1-mutant and LKB1-wild-type status at baseline is indicated. Colored points are significant (|log2 fold change| >0.5, FDR < 0.05). e. LKB1-deficiency score by RNA-seq (using 16-gene signature from Kaufmann et al., 2017) compared to log10(number of differential ATAC-seq peaks + 1) following LKB1 expression in each indicated cell line. Pearson correlation indicated in top left. Shaded area represents 95th percent confidence interval. f and g. Relative chromVAR deviation scores for SOX (f) an NR4A (g) motifs in the indicated cell lines transduced with GFP, LKB1, or KEAP1. Scores are normalized based on the GFP control for each cell line. N = 2 technical replicates per cell line and overexpression condition. h. Percent of differential ATAC-seq peaks (|log2 fold change | >0.5, FDR < 0.05) in cells transduced to express KEAP1 compared to GFP.Extended Data Fig. 7 Genotype-specific activation of SOX17 in LKB1-deficient metastatic cells.a. Percent survival of KPT and KPT;Lkb1−/− mice compared to KT mice. b and c. Number of primary tumors observed in KPT and KPT;Lkb1−/− mice (b). Lung weights of KPT and KPT;Lkb1−/− mice (c). N = 7 biologically independent mice for each genotype. Box-whisker plot; lower whisker is the lowest value greater than the 25% quantile minus 1.5 times the interquartile range (IQR), the lower hinge is the 25% quantile, the middle is the median, the upper hinge is the 75% quantile and the upper whisker is the largest value less than the 75% quantile plus 1.5 times the IQR. n.s. = non-significant with a two-sided t-test. d. Metastatic rates of KPT (2/7 mice with metastases) and KPT;Lkb1−/− (7/7 mice with metastases). p-value = 0.00016 with a one-sided binomial test. e and f. Comparison of the changes in motif accessibility (∆chromVAR deviation scores) between murine LKB1-proficient (KPT) and LKB1-deficient (KPT;Lkb1−/−) metastases (y-axis) and between murine LKB1-restored and LKB1-deficient cells (x-axis; e) or Chromatin Type 1 tumors and Chromatin Type 2 tumors (x-axis; f). Dark grey or colored points are called significantly different (q < 0.05) across both comparisons. Light grey points are not significant. A selection of motif families and their associated motif logos are indicated. g. log2 fold change in mRNA expression (left) and accessibility within the gene body (right) of each NKX2 transcription factor compared to the average expression and accessibility in primary tumor samples. Asterisks indicate transcription factors with greater than log2fold change of −1 in both RNA and ATAC measurements. h. log2 fold change in mRNA expression (left) and accessibility within the gene body (right) of each SOX transcription factor compared to the average expression and accessibility in primary tumor samples. Asterisks indicate transcription factors with greater than log2fold change of 2 in both RNA and ATAC measurements.Source dataExtended Data Fig. 8 LKB1-deficient primary tumors harbor sub-populations of SOX17 + cells.a. Representative immunohistochemistry (IHC) against SOX17 and grading of SOX17 expression for LKB1-proficient KPT and LKB1-deficient KPT;Lkb1−/− samples. Images are annotated according to percent area of the tumor composed of SOX17 + cells. Negative (0%), low (<25%), medium (25–50%), and high (>50%). Scale bars represent 50uM. Images are representative of 117 KPT primary tumors, 203 KPT;Lkb1−/− primary tumors, 14 KPT metastases, and 8 KPT;Lkb1−/− metastases, as quantified in (b). b. Quantitation of SOX17 protein expression in LKB1-proficient KPT and LKB1-deficient KPT;Lkb1−/− primary tumors and metastases, graded according to (a). The number of samples analyzed for histology for each genotype and tumor type is indicated at the top. Overall 0% of LKB1-proficient primary tumors or metastases had SOX17 + cells, 31% of LKB1-deficient primary tumors had SOX17 + cells, and 100% of LKB1-deficient metastases had SOX17 + cells. c. Correlation of SOX17 mRNA expression (y-axis) and LKB1 mRNA expression (x-axis) in ten human lung adenocarcinoma samples that contain Type 1 metastatic cell clusters (H0 and H3; Laughney et al. 2020). Each point indicates the mean value of SOX17 or LKB1 expression for each sample +/− SEM for all single cells evaluated by scRNA-seq. Shaded area represents 95th percent confidence interval. d. SOX17 genome accessibility track of the average ATAC-seq signal from Chromatin Type 1 and Chromatin Type 2 tumors.Source dataExtended Data Fig. 9 A subset of LKB1-deficient primary tumors harbor metastatic-like, SOX17 + sub-populations.a. scATAC-seq quality control metrics. TSS enrichment (left, middle), insertion profiles (right), and number of fragments per cell (right inset) in seven primary tumors. N = 998 cells for 10 C, 3556 cells for 13B, 1467 cells for 13 A, 3373 cells for 15 A, 1310 cells for 15B, 2858 cells for 17 A, and 851 cells for 21 A. Box-whisker plot; lower whisker is the lowest value greater than the 25% quantile minus 1.5 times the interquartile range (IQR), the lower hinge is the 25% quantile, the middle is the median, the upper hinge is the 75% quantile and the upper whisker is the largest value less than the 75% quantile plus 1.5 times the IQR. b. UMAP of cells from seven primary tumors. c. Percent of cells from each cluster in each primary tumor. d. Comparison of the changes in motif accessibility (∆chromVAR deviation scores) between LKB1-deficient metastases and primary tumors (y-axis) versus the average difference between cluster 12 cells and cells in clusters 1–11 (x-axis). Dark grey or colored points are called significantly different (q < 0.05) across both comparisons. Light grey points are not significant. e and f. Average accessibility of peaks in each scATAC-seq cluster that are enriched in LKB1-deficient primary tumors compared to LKB1-deficient metastases (e) or enriched in LKB1-deficient metastases compared to LKB1-deficient primary tumors (f) and are overlapping with the scATAC-seq peakset. Error bars indicate +/− SEM. N = 2993 cells (Cluster 1), N = 1011 cells (Cluster 2), N = 508 cells (Cluster 3), N = 856 cells (Cluster 4), N = 408 cells (Cluster 5), N = 3435 cells (Cluster 6), N = 468 cells (Cluster 7), N = 1517 cells (Cluster 8), N = 1733 cells (Cluster 9), N = 119 cells (Cluster 11), N = 116 cells (Cluster 12). Box-whisker plot; lower whisker is the lowest value greater than the 25% quantile minus 1.5 times the interquartile range (IQR), the lower hinge is the 25% quantile, the middle is the median, the upper hinge is the 75% quantile and the upper whisker is the largest value less than the 75% quantile plus 1.5 times the IQR.Extended Data Fig. 10 SOX17 regulates chromatin accessibility state and growth in metastatic, LKB1-deficient cells.a. Sox17 genome accessibility track (left) and mean mRNA expression (right) following 4-OHT or vehicle. Significantly differential ATAC-seq peaks in grey (log2 fold change < −0.5, FDR < 0.05). Sox17 also has significantly decreased mRNA expression (log2 fold change < −1, FDR < 0.05). b. GREAT GO term enrichment of genes nearby the differential peaks that contain SOX binding motifs. c. Sox17 genome accessibility track of an LKB1-restorable cell line (LR1;Cas9) transduced with the indicated sgRNAs and treated with 4-OHT or vehicle. d. Relative Sox17 mRNA expression in LR1;Cas9 cells transduced with sgSafe or sgSik1-3 and treated with either vehicle or 4-OHT. Mean values +/− SEM. N = 3 biologically independent samples examined over 2 experiments. e. Expression of SOX17 and/or LKB1 by immunoblot in LR2;Cas9 cells transduced with non-targeting (sgNT#1 and sgNT#2) or Sox17-targeting sgRNAs (sgSox17#1 and sgSox17#2) (top) or LR2;Cas9 cells transduced with BFP-overexpressing (control) or Sox17-overexpressing constructs and treated with vehicle or 4-OHT. HSP90 is a sample processing control. f. Heatmap of relative log2fold changes of the indicated genotypes of LR2;Cas9 cells. The top 10,000 consistent, variable ATAC-seq peaks following LKB1 restoration in both sgSafe and BFP transduced cells are shown. Clusters 3 and 4 from the Sox17 knock-out experiment are shown independently for emphasis in Fig. 5d. g and h. Lung weight following injection of LR2;Cas9 cells treated with vehicle or 4-OHT after Sox17 knock-out (g) or Sox17 overexpression (h). *p < 0.05, **p < 0.005, ***p < 0.0005 with a two-sided t-test. N = 3 biologically independent mice evaluated for LKB1-deficient (sgSafe) and 4 biologically independent mice for all other conditions. p = 0.0481 for sgSafe vs. sgSox17-1 (LKB1-deficient), p = 0.0184 for sgSafe vs. sgSox17-2 (LKB1-deficient), p = 0.0008 for BFP-vehicle vs. BFP-4-OHT, and p = 0.001 for BFP-4-OHT vs. Sox17-4-OHT. i. Schematic of intrasplenic (i.s.) injections into immunocompromised NSG mice. j. Representative fluorescent tdTomato+ images of the left lateral lobe of the liver. Scale bars represent 5 mm. k. Log10 (number of liver metastases) following intrasplenic injection of cells. Condition +/− SEM is shown. p = 0.055 with a two-sided t-test. N = 9 mice BFP, N = 8 mice for Sox17.Source dataSupplementary informationSupplementary InformationInformation on how to perform more detailed ATAC–seq analyses.Reporting SummarySupplementary Table 1Enriched sgRNAs and gene targets in LKB1-restored cells compared with LKB1-deficient cells from a genome-scale CRISPR–Cas9 screen. P values are calculated from a negative binomial model using the MAGeCK algorithm.Supplementary Table 2List of all ATAC–seq and scATAC–seq samples processed in this study with related quality control information.Supplementary Table 3Gene expression changes in LKB1-restorable and LKB1-unrestorable cell lines after treatment with 4-OHT or vehicle.Supplementary Table 4sgRNA spacer sequences used in this study.Supplementary Table 5List of all KPT and KPT;Lkb1−/− mouse samples processed for ATAC–seq in this study.Supplementary Table 6Gene expression of LKB1-proficient KPT and LKB1-deficient KPT;Lkb1−/− mouse primary tumours and metastases.Source dataSource Data Fig. 6Statistical source data.Source Data Extended Data Fig. 1Statistical source data.Source Data Extended Data Fig. 1Unprocessed western blots.Source Data Extended Data Fig. 7Statistical source data.Source Data Extended Data Fig. 8Statistical source data.Source Data Extended Data Fig. 10Statistical source data.Source Data Extended Data Fig. 10.Unprocessed western blots.Rights and permissionsReprints and permissionsAbout this articleCite this articlePierce, S.E., Granja, J.M., Corces, M.R. et al. LKB1 inactivation modulates chromatin accessibility to drive metastatic progression.

Nat Cell Biol 23, 915–924 (2021). https://doi.org/10.1038/s41556-021-00728-4Download citationReceived: 20 July 2020Accepted: 05 July 2021Published: 02 August 2021Issue Date: August 2021DOI: https://doi.org/10.1038/s41556-021-00728-4Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard

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Nat Rev Cancer. Author manuscript; available in PMC 2010 Feb 1.Published in final edited form as:Nat Rev Cancer. 2009 Aug; 9(8): 563–575. doi: 10.1038/nrc2676PMCID: PMC2756045NIHMSID: NIHMS144019PMID: 19629071The LKB1-AMPK pathway: metabolism and growth control in tumor suppressionDavid B. Shackelford1 and Reuben J. Shaw1,2David B. Shackelford1Dulbecco Center for Cancer Research, Molecular and Cell Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA 92037Find articles by David B. ShackelfordReuben J. Shaw1Dulbecco Center for Cancer Research, Molecular and Cell Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA 920372Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA 92037Find articles by Reuben J. ShawAuthor information Copyright and License information PMC Disclaimer1Dulbecco Center for Cancer Research, Molecular and Cell Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA 920372Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA 92037Correspondence: Reuben J. Shaw, Tel: 858-453-4100 ext. 1258, ude.klas@wahsPMC Copyright notice The publisher's final edited version of this article is available at Nat Rev CancerAbstractIn the past decade, studies of the human tumor suppressor LKB1 have uncovered a novel signaling pathway that links cell metabolism to growth control and cell polarity. LKB1 encodes a serine/threonine kinase that directly phosphorylates and activates AMPK, a central metabolic sensor. AMPK regulates lipid, cholesterol and glucose metabolism in specialized metabolic tissues such as liver, muscle, and adipose, a function that has made it a key therapeutic target in patients with diabetes. The connection of AMPK with several tumor suppressors suggests that therapeutic manipulation of this pathway with established diabetes drugs warrants further investigation in patients with cancer.IntroductionA fundamental requirement of all cells is that they couple the availability of nutrients to signals emanating from growth factors to drive proliferation only when nutrients are in sufficient abundance to guarantee successful cell division. Although a connection between cellular metabolism and tumorigenesis was first proposed 100 years ago by Otto Warburg, the molecular mechanisms interconnecting the signaling pathways controlling metabolism and cell growth have only begun to be decoded in the past decade, making this an active area of investigation in cancer research. One of the newly uncovered links directly connecting cell metabolism and cancer came from the discovery that that the serine/threonine kinase LKB1 (Liver Kinase B1; also known as Serine/Threonine Kinase 11 - STK11), a known tumor suppressor, was the key upstream activator of the AMP-activated protein kinase (AMPK)1-4. AMPK is a central metabolic switch found in all eukaryotes that governs glucose and lipid metabolism in response to alterations in nutrients and intracellular energy levels.LKB1 was identified originally as the tumor suppressor gene on human chromosome 19p13 responsible for the inherited cancer disorder Peutz-Jeghers Syndrome (PJS)5. Importantly, LKB1 is also one of the most commonly mutated genes in sporadic human lung cancer, particularly in multiple subtypes of non-small cell lung carcinoma (NSCLC)6, where at least 15-35% of cases have this lesion7. LKB1 was also recently found to be somatically mutated in 20% of cervical carcinomas8, making it the first known recurrant genetic alteration in this cancer which is caused by the human papilloma virus. Together, LKB1 and AMPK control cell growth in response to environmental nutrient changes, which, as we discuss in this Review, potentially identifies new targets and drugs for cancer therapy owing to the fact that the activity of AMPK can be targeted with drugs already in use for diabetes treatment. In addition to controlling cell growth and metabolism, both LKB1 and AMPK play conserved roles in cell polarity, disruption of which is also implicated in carcinogenesis. As LKB1 is one of the few serine/threonine kinases known to be inactivated through mutation during carcinogenesis, a critical early question lay in the identification of its substrates.LKB1 is a master kinaseThe search for substrates of LKB1 that mediate its tumor suppressor function led to the identification of AMPK as a direct substrate1-4. AMPK is a heterotrimer composed of a catalytic (AMPKα subunit and two regulatory (AMKPβ and AMPKγ) subunits (Fig. 1). AMPK is activated when intracellular ATP declines and intracellular AMP increases, such as during nutrient deprivation or hypoxia. Biochemical and genetic analyses in worms, flies and mice have revealed that LKB1 is the major kinase phosphorylating the AMPKα activation loop under conditions of energy stress9.Open in a separate windowFigure 1Schematic of the proteins in the LKB1 and AMPK kinase complexesBoth LKB1 and AMPK exist in heterotrimeric protein complexes. Inactivating mutations in LKB1 underlie the inherited cancer disorder Peutz-Jeghers Syndrome. Most mutations affect the function of the kinase domain, indicating that the tumor suppressor function of LKB1 requires its kinase activity. In addition to deletions or frameshifts, several missense mutations have been found and most cluster to the kinase domain resulting in loss of kinase activity. A handful of mutations lie outside the kinase domain and some of these have been shown to result in decreased kinase activity due to disruption of protein-protein interactions between LKB1 and its regulatory subunits STRAD (STE20-related adapter protein) and Mo25, which appear to be necessary for its kinase activity186. Together, the genetic evidence indicate that the tumor suppressor function of LKB1 requires its kinase activity. While there is a single LKB1 gene in mammals, two STRAD and two Mo25 family members exist and mutations in STRADα underlie the development of an inherited epileptic disorder187. There are two known splice forms of LKB1 differing in the very C-terminal amino acids188, 189, and evidence suggests STRAD proteins undergo extensive alternative splicing as well190. Like LKB1, AMPK is composed of a catalytic subunit (α) and two regulatory subunits. The beta subunits contain a conserved glycogen binding domain which also modulates AMPK activity191. The gamma subunits contain a series of tandem repeats of crystathionine-β-synthase (CBS) domains to which molecules of AMP directly bind as revealed in recent X-ray crystallography studies192. Binding of AMP to AMPKγ is thought to promote phosphorylation of the critical activation loop threonine (Thr172) in AMPKα, which is required for AMPK activity, largely through suppression of phosphatase activity towards Thr172193. Mutation of some of these AMP-binding pockets in the AMPKγ2 gene lead to hypertrophic cardiomyopathy that is associated with Wolff-Parkinson-White syndrome194.LKB1 also phosphorylates and activates 12 kinases closely related to AMPK10, 11 (Fig. 2). Of the 14 kinases, most current data suggest that only AMPKα1 and AMPKα2 are activated under low ATP conditions, probably because only they interact with AMPKγ12. Interestingly, four of these 14 kinases are mammalian members of the MAP/microtubule affinity regulating kinase (MARK)/Par-1 family, which are mammalian homologs of the C. elegans par-1 kinase that is required for early embryonic partitioning and polarity. Par-4 encodes the C. elegans ortholog of LKB113. The ability of LKB1 (or its orthologs) to act as master upstream kinases that activate AMPK, MARK/par-1, and several additional AMPK-related kinases appears to be widely conserved across eukaryotes.Open in a separate windowFigure 2LKB1-dependent signalingLKB1 in complex with its two regulatory subunits STRAD and Mo25 directly phosphorylates and activates a family of 14 AMPK-related kinases. These kinases in turn directly phosphorylate a number of downstream substrates to mediate effects on cell polarity, metabolism, and growth control. All well-established substrates of AMPK and its related family members are shown, and those for which further in vivo data is needed are shown with a question mark. It is important to note that many of the known substrates are expressed in a tissue-specific manner and may not explain ubiquitous effects of LKB1 and its downstream kinases in all cell types. Bottom: The sequences flanking the best-characterized phosphorylation site in each substrate with those residues selected for from in vitro peptide library and alanaine scanning peptide mutagenesis studies highlighted. Importantly, to date there is no substantive mutational data from human tumors to specifically support any of the downstream kinases, including the two AMPK catalytic genes, as being a particularly critical target of LKB1 in tumor suppression. One confounding issue with the lack of mutations found in these downstream kinases is that there is a great deal of redundancy among them, suggesting that loss of any one of them may be compensated for by other family members, unlike the case for LKB1 for which no other specific kinase has been shown to compensate in vivo.From tissue-specific knockouts of LKB1 in mice (Table 1), it appears that LKB1 dictates most of the AMPK activation in all tissues examined thus far, with the exception of some hypothalamic neurons14, T-cells15, and endothelial cells16 in which CAMKK2 appears to play a key role, although only in response to changes in the concentration of calcium17-19. Thus LKB1 uniquely mediates the prolonged and adaptive activation of AMPK following energy stress, which allows it to serve as a metabolic checkpoint.Table 1Genetically engineered mouse models of Lkb1 function in tumorigenesisTissue examinedTransgenic mouse modelPhenotypeSignificanceRefHeterozygous throughoutLkb1+/-Benign GI hamartomasMulti-focal osteoblastomas, paralysisGenetic and histological phenocopy of PJS - evidence for unexpected role in bone?115-8195Heterozygous throughout combined with p53 lossLkb1+/-, p53-/-Lkb1+/- or Lkb1+/-, p53+/-GI hamartomas greatly accelerated hepatocellular carcinomas in one strainp53 loss cooperatesInfectious agent or strain difference?19719610% function thoughoutLkb1 hypomorphNo tumor phenotype10% LKB1 thoughout but still no tumors so unlikely polyps haploinsufficient-unless this hypomorph has compensation13710% function thoughout & Pten heterozygousLkb1 hypomorph X Pten +/-Lymphomagenesis greatly accelerated compared to Pten +/-In presence of reduced Pten, 10% LKB1 not enough to prevent tumorigenesis137GI smooth muscle cellsSM22-Cre-Lkb1lox/+ or lox/losBenign GI hamartomasGI Polyps arising from smooth muscle - not epithelium?119Adult GI epitheliumCyp2a1- Lkb1lox/loxAltered differentiation of Paneth and goblet cells in adult GIAltered differentiation? Is deletion in relevant cell population for polyps?198Lung epitheliumLox-Stop-Lox-KrasG12D, Lkb1lox/lox delivered by inhalation of adeno-CreNon-small cell lung cancer: aggressive lung tumors of adeno-, squamous,& large cell origin; metastasis.LKB1 highly synergizes with K-ras mtAppearance of Squamous tumors / metastasis in adenocarcinomas7Endometrial epitheliumLkb1+/-Lkb1lox/loxintrauterine inject. of adeno-CreInvasive endometrial adenocarcinomaEndometrium highly sensitive to LKB1?121Prostate epitheliumP450CYP1A1-Cre-Lkb1lox/loxProstate hyperplasia & neoplasiaSex-hormone regulated growth affected?199Skin EpitheliumLkb1+/- with DMBA administered to skinK14-Cre-Lkb1lox/lox with or withoutDMBA administered to skinSquamous cell carcinoma of skin (and occasionally lung)LKB1 highly synergizes with H-ras mutations induced by DMBA?124Pancreatic precursorsLkb1+/- or Pdx1-Cre-Lkb1lox/loxBenign pancreatic cystadenomasAltered junctions, development200Open in a separate windowA LKB1-AMPK-mTORC1 checkpointPrior to its identification as a substrate for LKB1, AMPK was known to regulate lipid, cholesterol and glucose metabolism in specialized metabolic tissues such as liver, muscle and adipose20. Work from several laboratories in the past 5 years has revealed that one of the major growth regulatory pathways controlled by LKB1-AMPK is the mammalian target-of-rapamycin (mTOR) pathway. mTOR is a central integrator of nutrient and growth factor inputs that controls cell growth in all eukaryotes and is deregulated in most human cancers21.mTOR is found in two biochemically and functionally discrete signaling complexes22. mTOR complex 1 (mTORC1) includes raptor, which acts as a scaffold to recruit downstream substrates such as 4EBP1 and ribosomal S6 kinase (p70S6K1) that contribute to mTORC1-dependent regulation of protein translation23. mTORC1 controls the translation of a number of cell growth regulators, including cyclin D1, hypoxia inducible factor 1a (HIF-1α, and c-myc, which in turn promote processes including cell cycle progression, cell growth and angiogenesis, all of which can become deregulated during tumorigenesis21. mTORC1 is nutrient-sensitive and acutely inhibited by rapamycin, though recent studies reveal that rapamycin does not fully suppress mTORC1 activity in many cell types24-26. In contrast, mTORC2 contains the rictor subunit and is neither sensitive to nutrients nor acutely inhibited by rapamycin21.Cancer genetics and Drosophila genetics led to the discovery of upstream components of mTORC1 including the tuberous sclerosis complex 2 (TSC2) tumor suppressor and its obligate partner TSC1 27. TSC2 inhibits mTORC1 indirectly via regulation of the small GTPase Rheb, such that loss of TSC1 or TSC2 leads to hyperactivation of mTORC128. When levels of ATP, glucose or oxygen are low, AMPK directly phosphorylates TSC2 on conserved serine sites29-32and primes serine residues close by for subsequent phosphorylation by GSK-333. Wnt signaling inhibits phosphorylation of TSC2 by GSK-3, making TSC2 activity a biochemical coincidence detector of the activation state of AMPK and GSK-3 that dictates the amount downstream mTORC1 signaling.While TSC2 is clearly a central receiver of inputs that regulate mTORC1, cells lacking TSC2 still partially suppress mTORC1 following AMPK activation34, 35. In agreement with these data, raptor has been identified as a direct substrate of AMPK in vivo. Phosphorylation of two conserved serines in raptor by AMPK induced binding to 14-3-3 and resulted in suppression of mTORC1 kinase activity35. Phosphorylation of raptor was shown to be required for downregulation of mTOR and efficient G2/M cell cycle arrest following AMPK activation35. Taken together, the current data indicate that energy stress results in LKB1-dependent activation of AMPK, which directly phosphorylates both TSC2 and raptor to inhibit mTORC1 activity by a dual mechanism, although it remains possible that additional substrates of AMPK contribute to the regulation of mTOR (Fig. 3). Importantly, mTORC1 is currently the only signaling pathway downstream of LKB1 that has been shown to be deregulated in tumors arising in humans and mouse models of both Peutz-Jeghers syndrome31, 36 and NSCLC7, 37.Open in a separate windowFigure 3AMPK and PI3K signaling converge to antagonistically regulate a number of downstream effectors, including the mTORC1 complexA number of inherited hamartoma and cancer predispotion syndromes all share in common hyperactivation of mTORC1 or HIF-1α. Tumor suppressors inactivated in human cancer shown in light blue, oncogenes hyperactivated in human cancer shown in gold. Conditions that lower intracellular ATP levels (low glycolytic rates from low glucose or inhibitors like 2-deoxyglucose [2DG] or oxidative phosphorylation inhibitors like metformin and related biguanides) will lead to activation of AMPK in an LKB1-dependent manner. AICAR is a precursor of ZMP, which acts as an AMP-mimetic and is thought to directly bind the AMP-binding pockets of the AMPKγ subunit. A769662 is the only known small molecule that directly binds AMPK inducing its activity, though it is not currently known where the compound binds on the AMPK heterotrimer.LKB1-AMPK control of other growth regulatorsLKB1 has also been reported to regulate other key cancer-related pathways beyond mTORC1. Most notably, several connections have been made between LKB1, AMPK and the tumor suppressor p53. Before any direct substrates for LKB1 were identified, LKB1 reconstitution into LKB1-deficient tumor cells was reported to stimulate p53 activity and increase levels of Cdkn1a mRNA, which encodes the cyclin dependent kinase inhibitor p2138, 39. In addition, AMPK has been shown to modulate p53-dependent apoptosis40 and directly phosphorylate p53 on serine 1541, which is the established p53 site phosphorylated by the ATM, ATR and DNA-PK DNA-damage response kinases42. Several studies indicate that AMPK is also activated downstream of p5343 and this lead to the discovery of sestrin 1 and sestrin 2 — p53 target genes that inhibit mTOR signaling44. Overexpression of sestrin1 or sestrin 2 leads to increased AMPK activation and suppression of mTORC1 signaling, whereas mice that lack sestrin2 fail to downregulate mTORC1 following exposure to carcinogens. The molecular mechanism by which sestrins activate AMPK in this context remains to be fully elucidated. In addition to the sestrins, PRKAB1, which encodes the AMPKβ1 regulatory subunit, is a p53-responsive gene, suggesting another mechanism through which p53 can inhibit mTOR45.Importantly, AMPK has been demonstrated to phosphorylate a conserved serine in FOXO3a, the transcriptional factor targeted by PI3K/Akt signaling which plays key roles in cell survival and metabolism46. Of note is that the best mapped AMPK site in FOXO3a matches the consensus for 14-3-3 binding, which is also the case for the best mapped AMPK site in TSC2 (Fig. 2). The parallel regulation of both FOXO and mTOR signaling by AMPK and Akt signaling suggests further study is warranted into the functional overlap between these central pathways controlling both cell growth and metabolism.AMPK has also been reported to phosphorylate Thr198 of the cyclin dependent kinase inhibitor p2747, 48. However, Thr198 has also been reported to be phosphorylated by Rsk, Akt and Pim kinases, which promote cell growth. Why these pro-growth and anti-growth signals would both target the same phosphorylation site has yet to be established. Several additional AMPK substrates have been suggested to have a role in growth regulation49 50, however future studies with rigorously validated phospho-specific antibodies for each phosphorylation site and careful analysis of early time points following acute energy stress in wild-type or AMPK-deficient cells should help to assign which of these candidate targets are bona fide direct AMPK substrates in vivo.LKB1 and metabolism of glucose and lipidAlthough critical in the suppression of diabetes, the reprogramming of glucose and lipid metabolism by LKB1-dependent kinases is also likely to be important for the growth and tumor-suppressive effects of LKB1. AMPK acutely inhibits fatty acid and cholesterol synthesis through direct phosphorylation of the metabolic enzymes Acetyl-CoA carboxylase (ACC) and HMG-CoA reductase (HMGR)51. Thus activation of AMPK provides an endogenous mechanism to inhibit HMGR activity, akin to the pharmaceutical inhibition of HMGR by the statin family of compounds52. As ACC1 and HMGR are ubiquitously expressed, LKB1-deficient cells of all tissue types would be expected to exhibit enhanced rates of lipid and cholesterol synthesis. In line with recent RNAi studies showing that ACC1 and fatty acid synthase (FASN) are essential for survival in a number of cultured tumor cell lines53-55, chemical inhibitors of FASN and ACC have been shown to suppress the growth of prostate and lung cancer xenografts56, 57. Indeed, a variety of FASN inhibitors are being considered for clinical trails in cancer treatment58 and it remains plausible that suppression of lipogenesis is an important part of the tumor suppressor function of LKB1.Beyond these lipogenic enzymes, AMPK has been suggested to acutely modulate glycolysis though phosphorylation of multiple isoforms of phosphofructo-2 kinase (PFK2)59, 60. The data are particularly compelling for the inducible-PFK2 (PFKFB3) isoform, whose expression is dramatically upregulated in some types of human cancer61. Indeed, genetic ablation of Pfkfb3 in mouse lung fibroblasts suppressed KRAS-dependent transformation62 and small molecule inhibitors of PFKFB3 block the growth of lung cancer xenografts63.More broadly, LKB1-dependent kinases may also control cell growth and metabolism through phosphorylation of widely expressed transcriptional coactivators. The p300 histone acetyltransferase (HAT)64, several Class IIa histone deacetyltransferases (HDACs)65-67, and the CRTC (previously TORC)68-71 family of CREB coactivators have all been shown to be substrates of AMPK and related LKB1-dependent kinases (Fig. 2). Current data suggest that in response to distinct stimuli, subsets of LKB1-dependent kinases may target the same phosphorylation sites in these downstream effectors72. AMPK and its related kinases have been reported to phosphorylate Class II HDACs and CRTCs leading to their cytoplasmic sequestration and inactivation through 14-3-3 binding, similar to several other substrates of AMPK and its relatives. Though the best studied transcriptional targets of Class II HDACs and CRTCs are metabolic genes in muscle and liver respectively, these proteins may play wider roles in cell proliferation and tumorigenesis73 74. AMPK has recently been shown to enhance SIRT1 activity by increasing cellular NAD+ levels75, resulting in the regulation of many downstream SIRT1 targets including FOXO3 and PPAR gamma coactivator 1 (PGC1) (also known as PPARGC1A), both of which have also been proposed as direct substrates of AMPK46, 76. As SIRT1 itself is also implicated in tumorigenesis77, this connection between AMPK and SIRT1 may further illuminate how nutrients control cell growth.AMPK also suppresses mTOR-dependent transcriptional regulators to inhibit cell growth and tumorigenesis. Two mTORC1 regulated transcription factors involved in cell growth are the sterol-regulatory element binding protein 1 (SREBP-1) and hypoxia-inducible factor 1a (HIF-1α. SREBP-1 is a sterol-sensing transcription factor that drives lipogenesis in many mammalian cell types. mTORC1 signaling is required for nuclear accumulation of SREBP-1 and the induction of SREBP-1 target genes78 and this can be inhibited by rapamycin or AMPK agonists78, 79. Consistent with this, mice bearing a liver-specific Lkb1 deletion had increased expression of SREBP-1 target genes, and hepatic lipid accumulation and steatosis71. Moreover, SREBP-1 seems to be critical for cell growth in both Drosophila and mammalian cells78 suggesting that it may be an important target of LKB1, AMPK and mTOR signaling. Additional studies are needed to examine whether SREBP-1 is upregulated in LKB1-deficient tumors and how important SREBP-1 is for tumor formation under these conditions.HIF is a heterodimer composed of constitutive β (ARNT) subunits and α-subunits whose protein levels are stabilized through hypoxic inactivation of the von Hippel-Lindau (VHL) E3 ligase that targets HIF-α subunits for destruction80. In addition to being increased via hypoxia, HIF-1α protein levels are highly dependent on mTORC1 signaling. mTORC1 hyperactivation from mutations in oncogenes and tumor suppressors are sufficient to promote HIF-1α protein levels and expression of its downstream targets in mouse cancer models and cells in vitro81. Well-established HIF-1 transcriptional targets containing hypoxia-responsive elements (HREs) in their promoters include angiogenic factors such as VEGF and angiopoetin-2, a number of glycolytic enzymes, and multiple members of the GLUT family of glucose transporters82. In this fashion, HIF-1α activation in tumors may be responsible for the Warburg effect — the propensity of tumor cells to rely on glycolysis instead of oxidative phosphorylation83. Indeed, this regulation of glucose metabolism by HIF-1α contributes to tumorigenesis in multiple settings84, 85. Consistent with earlier studies in TSC-deficient fibroblasts86, we have recently shown that levels of HIF-1α and its targets GLUT1 and hexokinase are increased in LKB1- and AMPK-deficient fibroblasts in a rapamycin-reversible manner36. Similarly, the epithelium of gastrointestinal hamartomas from Peutz-Jeghers patients or Lkb1+/- mice (Table 1) also show increased expression of HIF-1α and HIF-1 target genes compared with the surrounding normal tissue, suggesting that Hif-1α may be a relevant target downstream of LKB1-deficiency in Peutz-Jeghers syndrome36. The increase in glucose uptake in tumours from patients with PJS could also be used to guide surgical resection of hamartomas in the GI tract. FDG-PET imaging studies on Lkb1+/- mice showed that their gastrointestinal hamartomas are specifically labeled in a rapamycin-sensitive manner. Given this, it will be interesting to examine whether the presence of LKB1 mutations dictates the level of FDG-PET signal in other tumor models, particularly in NSCLC and cervical cancer.LKB1-AMPK and cell polarityPar4, Par1 and Ampk Drosophila mutants have polarity defects during embryogenesis87-90 and oogenesis91. In mammalian cells, inducible activation of LKB1 is sufficient to promote full polarization of tumor cells, including apical and basolateral cell sorting, an actin cap and a full brush border, even in the absence of cell-cell contacts92. In cultured hippocampal neurons, overexpression of LKB1 induces multiple axons and RNAi depletion of LKB1 or its subunit STRAD block axonal differentiation93. Consistent with these findings, tissue-specific deletions in mice of LKB1 or brain-specific kinase 1 (BRSK1) or BRSK2 (orthologues of C.elegans SAD1 kinase and downstream targets of LKB1) result in loss of axonal specification during neuronal polarization in the developing mammalian cerebral cortex94. It is important to note that LKB1 does not appear to be required for polarization of all tissues, as several tissue-specific deletions of Lkb1 in the mouse do not show obvious disruptions of cellular polarity or tissue organization95. The requirement of LKB1 for establishment of polarity as opposed to maintenance of polarity is an additional consideration for the interpretation of these experiments. Cell polarity is known to be established through the action of a number of conserved antagonistic polarity protein complexes, and LKB1 and its downstream MARK/par-1 kinases contribute to this regulation (see Box 1).Box 1 Polarity protein complexesStudies across a wide range of metazoans have revealed that molecular control of cell polarity is commonly established through the opposing function of a handful of polarity protein complexes that mutually exclude the others’ localization172. In addition to LKB1 and the Par-1/MARK kinases, other highly conserved polarity genes include Par-3 and Par-6, which form a quaternary complex with the small GTPase cdc42 and atypical PKC (aPKC) subfamily of kinases (referred to as the “Par” complex). The binding of the small GTPase cdc42 to the Par complex results in activation of aPKC kinase activity, which in turn directly phosphorylates the MARK family of kinases on a conserved C-terminal threonine, leading to their association with 14-3-3 and exclusion from the apical domain of the cell178-180 (see Fig. 4). Reinforcing the mutual exclusion of the polarity complexes, the MARK kinases have been reported to directly phosphorylate and cause relocalization of the Discs Large (DLG) polarity proteins181 and the Par-3 scaffolding protein182. Whether this hypothesized mutual exclusion of the MARKs and Par complex can explain observed effects of LKB1 loss on GSK-3 and cdc42 activity in different settings183, 184 including NSCLC cell lines185 remains to be determined.LKB1 might also influence cell polarity and migration through a number of substrates of its downstream kinases involved in cytoskeletal remodelling. For example, MARK-dependent phosphorylation of microtubule associated proteins (MAPs) is thought to play a role in cell migration96 and may be relevant to the increased metastatic nature of NSCLC lung tumors specifically lacking LKB17. MARKs phosphorylate serine residues in the microtubule binding domain of MAPs, resulting in increased dynamic instability of cellular microtubules97.Another set of conserved MARK substrates are the Dishevelled (Dvl) proteins, which are key mediators of the Wnt signaling pathway98. Although MARK phosphorylation of Dvl regulates the membrane localization of Dvl, this is not required for canonical Wnt signaling in Xenopus99, and the MARK phosphorylation sites in Dvl do not seem to be required for the MARKs to affect Wnt signaling99, 100. This suggests that there must be additional unidentified MARK substrates involved in Wnt signaling. Interestingly, canonical and non-canonical Wnts were recently shown to induce cytoskeletal remodeling through Dvl binding to the Par complex, promoting atypical PKC mediated inactivation of the MARKs101-103. Thus Wnt-dependent signals, which promote tumorigenesis in several tissues including colon and breast cancer, may modulate LKB1-dependent signaling through multiple mechanisms, and vice-versa (see Fig. 4).Open in a separate windowFigure 4Control of cell polarity by LKB1-dependent signalingThe Par complex, composed of an atypical PKC family member, the Par-3 scaffold, the cdc42-binding Par-6, and cdc42 phosphorylates a number of downstream polarity proteins, including LKB1, the MARK family, and Lethal giant larvae (LGL). LKB1 also requires a signal from E-cadherin to be recruited and competent to phosphorylate AMPK at the adherens junction. LKB1-dependent AMPK activation is known to modulate the phosphorylation state of myosin light chain (MLC) in Drosophila mutants, which may be through indirect regulation of the kinase (MLCK) and phosphatase (MYPT1) for MLC. LKB1-dependent MARK kinases in turn phosphorylate the Par-3 scaffold, hence leading to the mutual exclusion of the Par complex and the MARK kinases within the cell. MARKs also are well-established to phosphorylate MAPs including tau, MAP2, and MAP4, and have been reported to phosphorylate DLG and Dishevelled (DVL) proteins in some contexts.AMPK has also recently been reported to modulate cell polarity in Drosophila and mammalian cells. AMPK activation in MDCK cells led to an increase in tight junctions104, 105 and treatment of a colon cancer cell line with the glycolytic inhibitor 2DG led to an AMPK-dependent increase in the number of polarized cells89. In addition, LKB1 and its regulatory subunit STRAD localize to adherens junctions in MDCK cells in an E-cadherin-dependent manner106. Loss of E-cadherin leads to specific loss of AMPK activation at adherens junctions. Studies of AMPK mutants in Drosophila showed mislocation of the Par complex as well as other polarity markers, including loss of myosin light chain (MLC) phosphorylation89. It was suggested in this paper that MLC may be a downstream substrate of AMPK; this seems unlikely as the sites do not conform to the optimal AMPK substrate motif found in all other established in vivo AMPK substrates. However, AMPK and its related family members have been reported to modulate the activity of kinases and phophatases that regulate MLC (MLCK107, MYPT1108), so the full molecular detail of the mechanism requires further study. Given the overlapping substrate specificity of AMPK and its related kinases (see Fig. 2), it seems likely that AMPK may control cell polarity by targeting some of the same substrates as other AMPK family members, such as the MARKs, phosphorylate under other conditions.Finally, it was recently shown that LKB1 promotes brush border formation on the apical surface of epithelial cells by the activation of the MST4 kinase. MST4 binds the LKB1 partner Mo25, and this interaction is conserved back through to budding yeast109. LKB1-dependent polarization resulted in MST4 translocation and subsequent phosphorylation of the cytoskeletal linker protein ezrin. This function of MST4 was needed for brush border induction but not other aspects of polarization.Whether the control of cell polarity plays any role in LKB1-dependent tumor suppression also awaits further study. Suggestive of its importance though was a recent study showing LKB1 RNAi in MCF10A mammary acini in 3-D culture led to a loss of polarity and promoted oncogenic mycdependent cell proliferation110, an effect that cannot be seen in standard tissue culture plates111-113. Dissection of the role of LKB1 in cell polarity is hence perhaps best examined in the context of mouse models of LKB1 deficiency.LKB1 and mouse models of cancerConsistent with the regulation of cell growth, metabolism and polarity, genetic studies on the loss of function of LKB1 in the mouse have revealed a number of cancerous phenotypes (see Table 1). Like PJS patients, mice heterozygous for Lkb1 develop gastrointestinal polyposis114-118. Strikingly, mice in which Lkb1 is specifically deleted in gastrointestinal smooth muscle cells also develop polyps much like Lkb1+/- mice 119. These mice had alterations in transforming growth factor β (TGFβ signaling, implicating this pathway in hamartoma formation 120 and have raised the possibility that loss of LKB1 in the smooth muscle compartment and not the epithelial cells might be the initiating event. Future studies are needed to further test this model. In addition to GI hamartomas, PJS patients are also predisposed to a number of other malignancies, including breast, ovarian, endometrial and pancreatic tumors, and some of these have been studied in specific Lkb1 mouse models (see table 1). Given the recent discovery of prevalent LKB1 somatic mutations in cervical cancer and their association with poor prognosis8, is it of particular note that deletion of LKB1 in endometrial epithelium of female mice results in highly invasive adenocarcinomas121.As LKB1 is frequently co-mutated with KRAS in NSCLC122, 123, mice bearing a conditional activated allele of Kras were crossed with mice bearing a conditionally inactivated allele of LKB1. The Kras;Lkb1lox/lox mice showed a dramatic increase in their tumor incidence and metastasis resulting in rapid acceleration of death (25 weeks for Kras alone vs. 10 weeks for Kras;Lkb1lox/lox)7. Furthermore, these mice develop all subtypes of NSCLC, as seen in humans, including squamous lung tumors which have not been previously observed in any genetic mouse model of lung cancer. Mechanistically, whether loss of LKB1 allows a distinct cell population to grow out and form squamous tumors or whether LKB1 loss impacts a lung stem cell compartment and alters their differentiation has yet to be investigated. Loss of LKB1 in skin keratinocytes was also recently reported to promote the development of squamous cell carcinomas, which was greatly accelerated by DMBA treatment124. Given the frequent mutation of Hras by DMBA, this further suggests that Ras-dependent signals and LKB1 loss may display a specific synergy that is selected for in tumour cells.Therapeutic ImplicationsAMPK agonists as cancer therapeuticsBecause of its long-established roles in various aspects of metabolic physiology, AMPK has received a great deal of pharmaceutical interest as a target for type 2 diabetes and other aspects of the metabolic syndrome125. Metformin (Glucophage), is the most widely used type 2 diabetes drug in the world and is thought to act by decreasing hepatic gluconeogenesis126. Metformin and its more potent analog phenformin inhibit complex I of the mitochondrial respiratory chain, resulting in reduced ATP production and LKB1-dependent activation of AMPK127. Indeed, this pathway is required for the therapeutic ability of metformin to lower blood glucose levels71. More recently, as metformin has been more widely prescribed for different diseases, for example, the treatment of insulin resistance in individuals with polycystic ovary syndrome, polymorphisms in LKB1 have been found in metformin non-responders128. More investigation is needed to determine the effect of these polymorphisms. Similarly, genetic polymorphisms in cell-surface transporter Oct1, which is required for efficient metformin uptake in hepatocytes, have been shown to underlie metformin resistance in some type 2 diabetics129.The fact that AMPK activation not only reprograms metabolism, but also enforces a metabolic checkpoint on the cell cycle through effects on p53 and mTORC1 signaling, suggests that AMPK activating drugs may be useful as cancer therapeutics. Interestingly, well before the mode of action or key targets of metformin were known, it had been shown to suppress naturally-arising tumors in transgenic mice and in carcinogen-treated rodent cancer models130, 131. More recently, metformin has been shown to inhibit the growth of a wide variety of tumor cells in culture in an AMPK-dependent manner132, 133 and AMPK activation by metformin or aminoimidazole carboxamide ribonucleotide (AICAR) suppresses the growth of tumor xenografts134-136. Similarly, treatment of ES cells with metformin results in growth suppression, an effect that is lost in LKB1-deficient ES cells137. Given the known pharmacokinetics and widespread long-term clinical use of metformin, its potential utility for chemotherapy deserves further attention. Phenformin is a more potent inhibitor of mitochondrial complex I and consequently more potently activates AMPK than metformin 138. Despite the withdrawal of phenformin from clinical use owing to the likely on-target side effect of fatal lactic acidosis 139, it might find modern utility as an anti-cancer agent as the dosing and duration of its use for cancer would be quite distinct from that for diabetes. The anti-tumor efficacy of metformin has been directly compared to that of either phenformin or the AMPK-binding140 small molecule Abbott A769662141 in Pten+/- mice that spontaneously-develop lymphomas. While all three compounds resulted in delayed tumor onset, phenformin and A769662 showed greater efficacy, which correlated with their ability to activate AMPK and suppress mTORC1 in a wider number of tissues in vivo than metformin137. Perhaps an additional key to the success observed in this study is the fact that tumors initiated through loss of Pten have activation of PI3K, making mTORC1 hyperactivation one of the biochemical initiating events for this tumor type and increasing the impact of suppression of mTORC1 from endogenous AMPK activation in these tumors. These data also suggest a possible therapeutic window for the use of AMPK agonists to treat tumors arising in patients with TSC or for tumors exhibiting hyperactivation of mTORC1 by other genetic lesions. The fact that the AMPK targeted Abbott compound also did well further suggests that AMPK is in fact a key target of the biguanides in tumor reduction.Given the number of type 2 diabetics worldwide taking metformin daily (>100 million), epidemiologists have begun examining the effect of metformin on cancer incidence. Initial studies revealed that diabetic patients taking metformin show a statistical reduction in tumor burden compared to patients taking any alternative142, 143. Similarly, a very recent study of breast cancer in type2 diabetics revealed a significant increase in complete pathological responses in patients taking metformin144, and a large phase III clinical trial of metformin as an adjuvant in breast cancer for diabetics and non-diabetics alike is in development145. Importantly, compounds that activate AMPK will not only impact tumor incidence through cell-autonomous effects on cell growth downstream of AMPK, but perhaps also through non-cell autonomous effects of lowering plasma insulin levels, which itself contributes to cancer risk and incidence146. Many additional epidemiological studies are required to determine whether there is indeed a clear tumor suppressive effect of prolonged use of metformin, and if so, whether tumors of specific tissues or bearing specific oncogenic lesions will show the greatest potential response. Critically, the OCT1 transporter which is critical for effective metformin transport into hepatocytes, shows a limited tissue distribution129 consistent with the pattern of AMPK activation in mice treated with metformin137. In contrast, a direct comparison of metformin to phenformin revealed that phenformin exhibited a more broad profile of tissues in which it potently activated AMPK137 indicating that for many tumor types in the whole organism, a direct action of metformin on tumor cells may be less likely than for phenformin. Interestingly, a recent study demonstrated that metformin was effective in treating a mouse model of endometrial hyperplasia and reducing mTORC1 signaling in that context147, though whether that effect was due to direct activation of AMPK in the endometrium or reduced circulating insulin and insulin signaling in the endometrium was not examined. Going forward, further attention needs to be placed on whether effects of metformin in mice and in human epidemiology studies can be attributed to indirect effects on lowered insulin levels from AMPK activation in liver (as will surely contribute in type 2 diabetics), or due to direct effects of AMPK activation in the tumor cells leading to suppression of their growth. These effects need not be mutually exclusive, and in fact are both likely to contribute to therapeutic effects of AMPK agonists on cancer risk.Even with effective targeting and activation of AMPK within tumor cells, as with other targeted therapeutics, AMPK activating drugs will likely be most useful against tumors of specific genotypes or in combination with other targeted therapeutics. In fact, tumor cells lacking LKB1 are hypersensitive to apoptosis in culture following treatment with energy stress inducing agents, presumably originating from an inability to restore ATP levels due to AMPK deficiency4, 37, 148, 149. Similarly, fibroblasts lacking TSC2 or p53 are also sensitive to apoptosis induced by energy stress28-30,40 and metformin and AICAR both preferentially killed isogenic colon cancer xenografts lacking p53 as opposed to those with intact p53 function135. Though energy stress can promote apoptosis in cells defective in the AMPK pathway, by contrast in cells competent for the AMPK pathway, its activation is well-established to promote cell survival47, 150, 151. Thus treatment of tumors with intact AMPK function with energy stress agents could lead to prolonged survival of tumor cells, consistent with the ability of AMPK promote survival of cells faced with metabolic stress imposed by activated oncogenes115, 152. These findings indicate that transient inactivation of AMPK may serve as a chemosensitizer in some tumor contexts, not unlike what has been proposed for drugs targeting the DNA damage checkpoint,153 which similarly dictates survival and apoptotic decisions following organismal stress.Therefore, defining which oncogenic genotypes (such as loss of p53 or LKB1) sensitize tumors to AMPK activating drug treatments in more refined genetically-engineered mouse tumor models within individual tumor types (lung, mammary, etc) is an important goal for future studies.Rapamycin as a therapeutic for hamartomas and other LKB1-deficient tumorsMutations in PTEN, NF1, TSC2, or LKB1 tumor suppressor genes are responsible for a number of inherited cancer syndromes, collectively referred to as phakomatoses. They all have overlapping clinical features including the development of hamartomas and aberrant pigmentation defects. Given that each of these tumor suppressors function upstream of mTORC1 (Fig. 3), the underlying hypothesis is that inactivation of these tumor suppressors in individual cells leads to cell-autonomous hyperactivation of mTORC1, ultimately resulting in tumors that are reliant on mTORC1 signaling. Over the past 5 years, rapamycin analogs have been examined in spontaneously arising tumors in Pten+/-154, Nf1+/-155, Tsc2 +/-156, Lkb1+/-36, 157, 158 and activated Akt84 transgenic mice and tumours in these mice have proven to be responsive to this approach.These encouraging preclinical results have helped spur ongoing phase II and phase III clinical trials for rapamycin analogs159, 160 161, 162. These data suggest that hamartoma syndromes involving hyperactivation of mTORC1 may be particularly responsive to rapamycin analogs as a single agent, although the effects might be cytostatic rather than cytotoxic161. Perhaps new, targeted inhibitors directed at the kinase domain of mTOR will produce greater therapeutic response with targeted cytotoxicity, or perhaps kinase inhibitors that inactivate both mTOR and PI3K would be even more effective, as PI3K provides a survival signal in most epithelial cell types.The number of patients with inherited hamartoma syndromes is dwarfed by the number of people with sporadic lung tumors containing LKB1 mutations. However, the predicted effectiveness of mTORC1 inhibitors against these tumors is unclear given that most of these tumors have mutated KRAS in addition to loss of LKB1, which might activate survival pathways other than mTORC1. Whether mTORC1 inhibitors might be useful in the treatment of LKB1 mutant tumors of different tissue origins remains to be determined.Outstanding questionsThe existence of a nutrient-regulated tumor suppressor pathway that couples cell growth to glucose and lipid metabolism raises a number of intriguing predictions and unanswered questions. For example, do environmental factors such as diet and exercise that contribute to physiological AMPK activation modulate tumorigenic risk through mTORC1 suppression? It is clear from a large number of epidemiology studies that cancer risk is correlated with metabolic syndrome, obesity or type 2 diabetes163. This association may be due to increased cell proliferation via hyperactivation of mTORC1 downstream of altered LKB1-AMPK signaling. The identity of the cell types most sensitive to growth suppression effects of AMPK and LKB1 may reveal those lineages in which cell growth is most tightly coupled to dietary conditions. Conversely, exercise and caloric restriction, each of which activates AMPK in some lineages, can lower overall cancer risk and improve cancer prognosis164. The mammalian cell types in which exercise and caloric restriction suppress cell growth and cancer risk remain to be delineated. Though much remains to be done to examine whether AMPK mediates some of the beneficial effects of exercise and caloric restriction on cancer risk, a recent study revealed that AMPK was activated, and mTORC1 signaling was suppressed, in some rodent tissues in a dose-dependent manner by increasing amounts of dietary restriction165. Conversely, high fat diet was observed to increase mTOR and decrease AMPK activity in some mouse tissues166. Finally, lower expression levels of metabolic hormones including the adipokine adiponectin — which is a key activator of AMPK in some tissues — have been shown to correlate with increased risk for breast endometrial, prostate and colon cancer167, 168. Strikingly, the incidence of colonic polyps in a colorectal cancer mouse model lacking adiponectin or the adiponectin receptor 1 (AdipoR1), was significantly increased and this correlated with loss of AMPK signaling and increased mTORC in the colonic epithelium169. These effects were only observed in animals on a high fat diet, further enforcing the concept that the metabolic status of the cells and the organism will dictate the conditions where LKB1 is most effective in tumor suppression.Whether the endogenous metabolic checkpoint imposed by AMPK must be subjugated to allow tumorigenic progression is also unclear. Melanoma cell lines expressing oncogenic BRAF do not activate AMPK following energy stress due to hyperphosphorylation of LKB1 at Erk- and Rsk-phosphorylation sites170. Moreover, Ampkα2 mRNA levels in breast and ovarian cancers are profoundly suppressed by oncogenic PI3K signals 171, suggesting another route through which AMPK signaling can be inhibited. Thus, there is evidence that oncogenic pathways can downregulate LKB1 and AMPK through a variety of mechanisms. When selection against the LKB1-AMPK pathway occurs is also unclear, but it is conceivable that limitations on glucose and oxygen diffusion in pre-angiogenic tumors will result in growth inhibition, possibly due to activation of an AMPK-mediated metabolic growth checkpoint. Whether endogenous AMPK signaling is truly part of the pre-angiogenic checkpoint is a crucial question. Furthermore, whether pre-angiogenic tumors lacking LKB1 or AMPK continue to proliferate faster than AMPK-containing counterparts but then succumb to apoptosis or necrosis due to the inevitable energy shortage remains to be seen. The role and requirement for AMPK in these processes and overall tumor suppression is perhaps best addressed genetically through deletion of AMPK subunits in the context of different well-studied mouse models of tumorigenesis.Despite the evidence supporting a role for AMPK as metabolic checkpoint in the cell, key mechanistic questions remain regarding which of the kinases downstream from LKB1, and which of their substrates, are required for tumor suppressor activity of LKB1 in different tissue settings. The regulation of mTORC1 and p53 by AMPK make it a likely contributor to LKB1-dependent tumor suppression. However, control of cell polarity is also known to play a role in tumorigenesis172 and in fact suppression of the MARK kinases by the Helicobacter pylori CagA protein is thought to be essential for its pathogenic disruption of gastric epithelial polarity and tumor promotion173. Currently there is minimal mutational data from human tumors to specifically support any single LKB1-dependent kinase as the critical target for LKB1 in tumorigenesis. There is a great deal of redundancy among them, suggesting that in many tissues loss of any one kinase may be compensated for by other family members.The potency of LKB1 as a tumor suppressor probably derives from its control of multiple growth suppressive pathways. For example, combined loss of LKB1 with KRAS in the mouse lung epithelium causes 3 discrete phenotypes: accelerated tumor progression and tumor growth; the appearance of a novel tumor type, squamous carcinomas; and a dramatic increase in the numbers of metastases. While AMPK and mTORC1 signaling may play a role in the growth component of this acceleration, it also seems probable that loss of cell polarity and increased cytoskeletal signaling upon loss of MARK activity impacts the unique metastatic nature of the LKB1-deficient tumors. The appearance of novel tumor types may also reflect de-differentiation through transcriptional reprogramming downstream of AMPK and several of its related family members. AMPK has also been shown to modulate other tumor suppressive mechanisms, including the promotion of autophagy174 and cellular senescence175 under energy-poor conditions. The absolute requirement for AMPK or LKB1 in the induction of senescence or autophagy in different physiological and pathological contexts in an intact organism remains to be fully investigated.Another important question is whether LKB1 or AMPK deregulation often contributes to the Warburg effect. Studies from cell culture and targeted mouse knockouts have revealed that mutations in oncogenes and tumor suppressors that drive tumorigenesis stimulate HIF-1α176. Indeed, HIF-1α and its target genes are upregulated in LKB1-, AMPK-, and TSC-deficient fibroblasts even under normoxic conditions, indicating that loss of any one of these genes is sufficient to confer activation of the full HIF-1α transcriptional program and hence alter cell metabolism36, 177. Indeed immunohistochemistry on gastrointestinal tumors from Peutz-Jeghers patients and LKB1+/- mice reveals that both contain elevated HIF-1α and its target GLUT1, and these tumors in LKB1+/- mice are positive by FDG-PET despite their benign nature36. These observations further prompt an examination of physiological or pathological contexts in which LKB1 or AMPK normally act to suppress HIF-1α and whether their inactivation is commonly involved in the glycolytic switch of most tumors. Given the regulation of the LKB1-AMPK pathway by hormones, exercise and diet, future studies should address whether LKB1 or AMPK mediate changes in tumor metabolism and FDG-PET imaging following behavioral or hormonal intervention. Whether LKB1 mutant NSCLC and cervical cancers show altered FDG-PET, and whether that can be used to direct therapeutic interventions in different patient populations, will be important aims for future studies. Regardless, the development of new serum and tissue biomarkers reflective of LKB1 and AMPK activation state will lead to better optimization of future clinical trials aimed at efficacy of targeted therapeutics.While these and many other questions will take years to fully address, the discovery of this highly conserved pathway has already led to fundamental insights into the mechanisms through which all eukaryotic organisms couple their growth to nutrient conditions and metabolism. A deeper understanding of the key components of this pathway will not only lead to future therapeutic targets for cancer and diabetes, but will reveal the minimal number of steps required to suppress cell growth and reprogram metabolism.AcknowledgementsWe regret being unable to cite the work of many of our colleagues owing to space limitations. The authors wish to thank Katja Lamia for critical reading and editing of the manuscript. The authors’ research is funded by grants from the NIH (R01 DK080425 and P01 CA120964), American Cancer Society, and V. Foundation for Cancer Research to R.J.S. D.B.S. was supported by training grant T32 CA009370 to the Salk Institute Center for Cancer Research. R.J.S. is an Early Career Scientist of the Howard Hughes Medical Institute.Glossary termsPeutz-Jeghers Syndrome (PJS)PJS is characterized by the development of gastrointestinal hamartomas and an increased predisposition to a number of other malignancies including those arising in colon, breast, ovarian, pancreatic and lung tissue.Tuberous sclerosis complex (TCS)A familial tumour syndrome induced through mutation of the mTORC1 regualators TSC1 and TCS2.SteatosisExcess intracellular lipid accumulation such as occurs pathologically in the liver in diabetic or obese patientsBiography• BiographyReuben J. Shaw is the Hearst Endowment Assistant Professor in the Molecular and Cell Biology Laboratory at the Salk Institute for Biological Studies. His laboratory, including postdoctoral fellow David B. Shackelford, study the role of LKB1 and AMPK in cancer and diabetes.195-197re198de199fin200 FootnotesAT A GLANCEThe LKB1 serine/threonine kinase is inactivated in Peutz-Jeghers syndrome and a large percentage of sporadic non small cell lung carcinomas and cervical carcinomasLKB1 acts a master upstream kinase, directly phosphorylating and activating AMPK and a family of 12 related kinases which play critical roles in cell growth, metabolism, and polarityThe LKB1/AMPK pathway serves as a metabolic checkpoint in the cell, arresting cell growth under conditions of low intracellular ATP such as under conditions of low nutrientsOne the central mitogenic pathways suppressed by LKB1 and AMPK signaling is the mTORC1 target of rapamycin pathway, which is inhibited via AMPK phosphorylation of TSC2 and raptorOrganismal metabolism and overnutrition can suppress LKB1-AMPK signaling which may contribute to increased cancer risk in obese or diabetic patients. 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v.2019; 2019

PMC6874879

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Oxid Med Cell Longev. 2019; 2019: 8730816. Published online 2019 Oct 31. doi: 10.1155/2019/8730816PMCID: PMC6874879PMID: 31781355LKB1/AMPK Pathway and Drug Response in Cancer: A Therapeutic PerspectiveFrancesco Ciccarese,# Elisabetta Zulato,# and Stefano IndraccoloFrancesco CiccareseIstituto Oncologico Veneto IOV-IRCCS, Padova, ItalyFind articles by Francesco CiccareseElisabetta ZulatoIstituto Oncologico Veneto IOV-IRCCS, Padova, ItalyFind articles by Elisabetta ZulatoStefano IndraccoloIstituto Oncologico Veneto IOV-IRCCS, Padova, ItalyFind articles by Stefano IndraccoloAuthor information Article notes Copyright and License information PMC DisclaimerIstituto Oncologico Veneto IOV-IRCCS, Padova, ItalyCorresponding author.#Contributed equally.Stefano Indraccolo: ti.dpinu@oloccardni.onafets Academic Editor: Cinzia DomenicottiReceived 2019 Apr 12; Revised 2019 Sep 10; Accepted 2019 Sep 16.Copyright © 2019 Francesco Ciccarese et al.This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.AbstractInactivating mutations of the tumor suppressor gene Liver Kinase B1 (LKB1) are frequently detected in non-small-cell lung cancer (NSCLC) and cervical carcinoma. Moreover, LKB1 expression is epigenetically regulated in several tumor types. LKB1 has an established function in the control of cell metabolism and oxidative stress. Clinical and preclinical studies support a role of LKB1 as a central modifier of cellular response to different stress-inducing drugs, suggesting LKB1 pathway as a highly promising therapeutic target. Loss of LKB1-AMPK signaling confers sensitivity to energy depletion and to redox homeostasis impairment and has been associated with an improved outcome in advanced NSCLC patients treated with chemotherapy. In this review, we provide an overview of the interplay between LKB1 and its downstream targets in cancer and focus on potential therapeutic strategies whose outcome could depend from LKB1.1. IntroductionThe Liver Kinase B1 (LKB1, also known as STK11) is a tumor suppressor gene encoding a ubiquitously expressed and evolutionarily conserved serine threonine kinase, originally associated with the inherited cancer disorder Peutz-Jeghers Syndrome [1, 2]. Inactivating somatic mutations of LKB1 are frequently reported in non-small-cell lung cancer (NSCLC) [3], malignant melanoma [4], and cervical carcinoma [5]. LKB1 positively regulates the AMP-activated protein kinase (AMPK) [6] and at least 12 additional AMPK-related downstream kinases, involved in the control of cell growth and metabolism and in the regulation of cellular response to energy stress and establishment of cell polarity [7]. Deregulation of LKB1 signaling has been implicated in oncogenesis across many cancer types [8–10], although the energy-sensing function of LKB1-AMPK may also confer a survival advantage under unfavourable conditions [11].Several preclinical studies identified LKB1 signaling axis as a potential modifier of response of cancer cells to different drugs. Thus, understanding the different mechanisms that account for anti- or prooncogenic effect of LKB1 is essential to identify therapeutic strategies targeting this pathway.In this review, we address the potential vulnerabilities of LKB1-deficient tumors and focus on recent scientific findings that support a role of this pathway in the modulation of drug response in cancer.2. LKB1 Alterations in Human CancersGermline loss of LKB1 kinase activity accounts for the Peutz-Jeghers Syndrome, an autosomal dominant inherited disorder characterized by hamartomatous polyps in the gastrointestinal tract and mucocutaneous pigmentation [2]. Peutz-Jeghers Syndrome is associated with age-related increased risk of cancer development, principally involving the gastrointestinal tract but affecting also the breast, gynecologic tract, lung, and other sites [12], corroborating a bona fide tumor suppressor role for LKB1.In the great majority of human cancers, somatic mutations of the LKB1 gene are rare. However, LKB1 is the most frequently mutated gene in cervical carcinoma (20% of cases [5]) and the third most mutated gene in NSCLC (30% of cases in the Caucasian population [13]). Frequent somatic LKB1 loss in lung adenocarcinoma is puzzling, as lung cancer is uncommon in Peutz-Jeghers patients. In contrast, LKB1 somatic mutations are rare in colorectal cancer [14], the most frequent neoplasia associated with inherited LKB1 loss. Several factors could account for these differences. First, LKB1 loss in NSCLC is frequently homozygous [15], indicating that probably monoallelic LKB1 in Peutz-Jeghers patients is sufficient to limit lung tumorigenesis. Second, LKB1 mutations coexist with several other genetic alterations in sporadic cancers. TP53 and KRAS are, respectively, the first and the second most mutated genes in lung adenocarcinoma. About 12% of NSCLC cases have LKB1 and KRAS comutations [16]. Moreover, LKB1 mutations cooccur with gain-of-function TP53 mutations in 8.2% lung adenocarcinomas [17]. Third, LKB1 mutations are associated with smoking history of NSCLC patients [18]. Fourth, by interacting with breast cancer susceptibility 1 (BRCA1), LKB1 is involved in the DNA damage response, promoting homologous recombination (Figure 1) and fostering genomic stability [19]. In light of these considerations, LKB1 loss could be induced by and, afterwards, facilitate the mutagenic properties of carcinogens contained in tobacco smoke, being selected to promote lung tumorigenesis, while other malignancies—such as colon cancer—have evolved different protumorigenic alterations.Open in a separate windowFigure 1LKB1-proficient tumors display coordinated control of metabolism, DNA repair, and mitochondrial dynamics. LKB1 interacts with the pseudokinase STE20-Related Kinase Adaptor Alpha (STRADα) and with the armadillo-repeat containing protein MO25α. Once activated, LKB1 phosphorylates AMPK, which coordinates activation of catabolic processes—such as glycolysis, Krebs cycle, pentose phosphate pathway, fatty acid oxidation, and autophagy—and inhibition of anabolic processes—such as fatty acid synthesis and mTOR pathway. This maximizes ATP production and NADPH regeneration, thus controlling energy and redox homeostasis. Moreover, AMPK promotes mitochondrial fusion and mitophagy of damaged mitochondrial portions. In the nucleus, LKB1 fosters genomic integrity through sustaining homologous recombination. Black arrows from AMPK: direct phosphorylation. Red arrows: activation/upregulation. Yellow circles: phosphate groups. Red phospholipids in membranes: peroxidised phospholipids. Red stars in the nucleus: DNA damage sites. G6P: glucose 6-phosphate; F6P: fructose 6-phosphate; F1,6BP: fructose 1,6-biphosphate; G3P: glyceraldehyde 3-phosphate; 1,3BPG: 1,3-biphosphoglycerate; 3PG: 3-phosphoglycerate; 2PG: 2-phosphoglycerate; PEP: phosphoenolpyruvate; Pyr: pyruvate; AcCoA: acetyl-coA; 6PG: 6-phosphogluconate; Ru5P: ribulose 5-phosphate; R5P: ribose 5-phosphate; GLUT: glucose transporter; GSH: reduced glutathione; GSSG: oxidized glutathione; H2O2: hydrogen peroxide; oxPPP: oxidative pentose phosphate pathway; TCA: tricarboxylic acid cycle; ETC: electron transport chain; FAO: fatty acid oxidation. The names of proteins deriving from disassembly of mTORC1 and NADPH oxidase complexes are omitted. See the text for details.An interesting feature of NSCLC is its intratumor heterogeneity. Remarkably, somatic LKB1 loss is an intermediate event during lung carcinogenesis, which arises clonally in lung cells with preexisting mutations in initiating drivers, such as TP53 and KRAS [20]. The subclonal nature of LKB1 highlights how the complexity of cancer genetics might impact on tumor progression and resistance to therapy.Considering all the genetic and epigenetic events that can affect the LKB1 gene, the estimated real frequency of LKB1 alterations in NSCLC is as high as 90% [15], hinting at its fundamental role in lung cancer biology. Moreover, it should be emphasized that the frequency of LKB1 loss in other cancer types could be underestimated, due to rarely investigated epigenetic alterations. A paradigmatic example is breast cancer, whose aggressiveness and metastasis are promoted by LKB1 loss [9], even if LKB1 mutations are detected with low frequency. The combination of sequencing and analysis of protein expression might overcome intrinsic limitations of sequencing and provide a comprehensive evaluation of LKB1 status in tumors.3. Role of LKB1-AMPK Pathway in Cell MetabolismLKB1 was identified as the critical upstream kinase required for AMPK activation [6, 21, 22] (Figure 1), thus providing a direct link between a known tumor suppressor and regulation of metabolism [23]. AMPK has a central role in the regulation of energy metabolism in eukaryotes and coordinates glucose and lipid metabolism in response to alterations in nutrients and intracellular energy levels, contributing to maintain steady-state levels of intracellular ATP [24].Upon changes in energy availability, causing perturbations in the ATP-to-ADP or ATP-to-AMP ratio, AMPK is activated by an allosteric mechanism and by LKB1 via phosphorylation [7]. AMPK is also activated by increases in intracellular Ca2+ [25–27] and by DNA damage [28–30]. Moreover, a novel AMP-independent mechanism of AMPK activation under glucose starvation has recently been described by Zhang and colleagues who observed that, upon glucose starvation and the consequent decrease of fructose-1,6-bisphosphate (FBP) levels, aldolases promote the formation of a lysosomal complex containing v-ATPase, Ragulator, AXIN/LKB1, and AMPK [31], leading to LKB1-mediated AMPK activation before energy levels fall. This aldolase-dependent mechanism of AMPK activation could be at play under conditions where low glucose does not cause an increase of intracellular AMP-to-ATP or ADP-to-ATP ratios.Once activated, AMPK redirects metabolism towards decreased anabolism and increased catabolism by phosphorylation of key proteins involved in several metabolic pathways [24], including lipid homeostasis, glycolysis, protein synthesis, and mitochondrial homeostasis.AMPK was originally defined as the critical inhibitory upstream kinase for the metabolic enzymes acetyl-CoA carboxylase (ACC1 and ACC2) [32] (Figure 1) and HMG-CoA reductase [33], which serve as rate-limiting steps for fatty acid and sterol synthesis, respectively, in a wide variety of eukaryotes. Moreover, inactivation of ACC2 switches on fatty acid (FA) β-oxidation in mitochondria [34]. Through activation of FA oxidation and inhibition of FA synthesis, LKB1-AMPK pathway plays a pivotal role in the maintenance of intracellular NADPH levels, which is required to prevent oxidative stress and to promote cancer cell survival under energy stress conditions [35].Moreover, when nutrient levels are low, AMPK acts as a metabolic checkpoint inhibitor of cell growth, by modulation of the master regulator of growth, the mammalian target of rapamycin (mTOR) pathway [36] (Figure 1). AMPK activation leads to inhibition of mTOR complex 1 (mTORC1), by activation of the negative mTORC1 regulator TSC2 and by inhibition of the mTORC1 subunit RAPTOR [36]. Importantly, activated mTORC1 is localized on the surface of lysosomes, where it is negatively regulated by AXIN through inhibition of the GEF (guanine nucleotide exchange factor) activity of Ragulator. Thus, AXIN/LKB1 complex inhibits mTORC1 through the glucose-sensing mechanism involving aldolase and FBP [31]. Moreover, AMPK activation caused G1 cell cycle arrest associated with activation of p53, followed by induction of the cell cycle inhibition protein p21 and by stabilization via phosphorylation of the cyclin-dependent kinase inhibitor p27kip1 [37, 38]. Through mTOR inhibition, AMPK downregulates hypoxia-inducible factor 1α (HIF-1α), thus counteracting the Warburg effect [39].In addition to its central role in the regulation of cell growth, mTORC1 controls autophagy, a lysosome-dependent catabolic program that maintains cellular homeostasis. Upon nutrient starvation, mTORC1 is inactivated through the energy-sensing mechanism of AMPK activation. Moreover, mTORC1 is also inhibited by direct dissociation from lysosomes through the glucose-sensing mechanism [31]. This mTORC1 suppression relieves the inhibitory phosphorylation on Unc-51-Like Autophagy Activating Kinase 1 (ULK1), a kinase essential for autophagy induction [40, 41]. AMPK has also an important role in the regulation of autophagy through direct phosphorylation of ULK1 and of a second autophagy-initiating regulator, the lipid kinase complex PI32KC3/VPS34 [42]. Interestingly, AMPK triggers acute destruction of dysfunctional mitochondria through ULK1-dependent stimulation of mitophagy (Figure 1), and it stimulates de novo mitochondrial biogenesis through peroxisome proliferator-activated receptor gamma coactivator 1 α- (PGC-1α-) dependent transcription [38]. Interestingly, genetic deletion of Lkb1 in the haematopoietic stem cell resulted in mitochondrial dysfunction and deregulation of bioenergetic processes through AMPK-dependent and independent mechanisms [43–45]. The interplay between AMPK and mitochondria is further discussed in a distinct section.Besides AMPK, other 12 kinases, collectively termed AMPK-related kinases, are LKB1 substrates. However, little is known about what stimuli direct LKB1 towards any of these AMPK-related kinases. These enzymes include two family members, SNARK/Nuak2 and SIK2, both activated under low energy conditions, although only AMPK is activated under low ATP levels [36]. Moreover, other members, such as isoforms of PAR1/MARK, as well as SAD/BRSK, unlike AMPK, are not activated by energy stress but have been implicated in controlling cell polarity [46].3.1. LKB1: An Unexpected Oncogenic Role for a Tumor SuppressorRecently, the role of LKB1-AMPK to sense different types of stress has pointed at a conditional oncogenic role of this pathway. In fact, its ability to modulate cell metabolism in order to restore homeostasis may confer a survival advantage under selective pressure, by favoring adaptation to hostile conditions [47]. In this context, Lee and colleagues demonstrated that polyubiquitination of LKB1 by S-Phase Kinase-Associated Protein 2 (Skp2) ubiquitin ligase promotes its persistent activation, leading to cell survival and poor outcome in hepatocellular carcinoma patients [48]. A recent study showed that, although it negatively regulates the epithelial-to-mesenchymal transition (EMT)-inducing gene ZEB1, LKB1 expression is increased in spheroids obtained from breast cancer cell lines and its ablation induces anoikis, suggesting that LKB1 promotes survival of circulating tumor cells [49]. LKB1 activation can result in an oncogenic program based on the contextual oncogenic role of its targets. For instance, LKB1 upregulates the expression of miR-34a [50], which was found to promote survival in the context of adult T-cell leukemia/lymphoma (ATLL) [51].Downstream of LKB1, also AMPK has been indicated as a contextual oncogene. In fact, AMPK activation promotes glioblastoma growth by inducing lipid internalization [52] and sustains bioenergetics of glioblastoma through HIF-1α signaling [53]. Moreover, AMPK activation results in increased AKT oncogenic signaling through Skp2 phosphorylation under stress [54] and promotes aberrant expression of PGC-1β and estrogen-related receptor α (ERRα) in colon cancer, supporting its survival [55]. Finally, AMPK activation promotes resistance of cancer cells to chemotherapy by induction of autophagy [56–59].How can the contrasting role of LKB1 as a tumor suppressor or promoter of cancer survival be reconciled? It must be considered that this pathway has evolved to allow cell survival under energy stress. During the initial phases of tumorigenesis, stress is a critical event that alters cell physiology and induces genetic aberrations, genomic instability, and transformation. In this context, LKB1 and AMPK play a tumor suppressor role by dealing with metabolic stress. The maintenance of genomic integrity, activation of autophagy, which scavenges damaged organelles and proteins, and activation of TP53 [14] to eliminate aberrant cells blunt cancer initiation. However, stress is a double-edged sword in cancer, and if not solved, it would lead to tumor eradication. In this scenario, a functional LKB1-AMPK pathway is advantageous for growing cancer cells, as it promotes adaption to a hostile microenvironment and cell survival. The activation of catabolic pathways and increased recycling of cellular components through autophagy ensure maintenance of energy homeostasis [60]. Autophagy, which has both prosurvival and prodeath effects, is probably the main responsible for contextual tumor suppressor and oncogenic activities of LKB1-AMPK. It should be pointed out, however, that autophagic cell death is a concept that should be cautiously evaluated. Cell death occurs, likely, despite autophagy, rather than because of autophagy [61]. In fact, increased autophagy in dying cells could be a rescue mechanism that failed or a mechanism sustaining apoptosis through ATP production. Physiologic “tumor suppressor” autophagy, which degrades damaged organelles and suppresses tumor initiation, should be distinguished by aberrant “prosurvival” autophagy, which is coopted by cancer to sustain its growth. As degradation of cellular components that have been damaged by anticancer therapies is a widely adopted mechanism of resistance, activation of autophagy by LKB1-AMPK in advanced stage cancers could represent a rescue mechanism.4. Mitochondrial Dynamics Is Affected by LKB1-AMPK PathwayAs master regulators of metabolism, LKB1 and AMPK are tightly intertwined with mitochondrial function and dynamics (Figure 1). Mitochondria are essential dynamic organelles that continuously shift from fusion to fission and vice versa. Mitochondrial dynamics is in part regulated by the LKB1-AMPK pathway (Table 1). Following stress, AMPK activates mitochondrial fusion to restore the function of damaged mitochondria. If the damage is too extensive, AMPK activates mitochondrial fission and mitophagy to separate and degrade damaged mitochondrial portions and promotes synthesis of new mitochondria, in order to preserve mitochondrial network function and maximize ATP production (Table 1). In contrast, in LKB1 defective tumors, hypoxic stress elicits activation of HIF-1α [62], which reduces the expression of Mitofusin-1 (MFN1) and Optic Atrophy 1 (OPA1) and increases activity of Dynamin-Related Protein 1 (DRP1), thus unbalancing mitochondrial dynamics towards fission (Figure 2). In endothelial cells, this promotes migration, invasion, and tube formation, implying that hypoxia-induced mitochondrial fission activates angiogenesis [63].Open in a separate windowFigure 2LKB1 loss alters cancer cell biology. LBK1 loss and consequent lack of AMPK activation lead to mTORC1 assembly, resulting in autophagy inhibition. High metabolic requirements imposed by sustained proliferation are met through aerobic glycolysis (i.e., Warburg effect), driven by HIF-1α stabilization, which provides cancer cells with ATP and intermediates for anabolic reactions (not shown). Pyruvate is preferentially converted to lactate, which is excreted in the tumor microenvironment. Activation of ACC1 and ACC2 promotes fatty acid synthesis in the cytosol, by using citrate coming from mitochondria. NOX1 expression drives the assembly of NADPH oxidase complex, which produces ROS in the microenvironment. NOX-produced ROS enter the cell, thus inducing oxidative stress and activating NRF2 through the oxidation of KEAP1. Reduced expression of MFN1 and OPA1 and increased activity of DRP1, induced by HIF-1α activation, lead to mitochondrial fragmentation. Increased ROS levels and mitochondrial fission promote the secretion of proangiogenic factors in the microenvironment. Yellow circles: phosphate groups. Red phospholipids in membranes: peroxidised phospholipids. Red stars in the nucleus: DNA damage sites. G6P: glucose 6-phosphate; F6P: fructose 6-phosphate; F1,6BP: fructose 1,6-biphosphate; G3P: glyceraldehyde 3-phosphate; 1,3BPG: 1,3-biphosphoglycerate; 3PG: 3-phosphoglycerate; 2PG: 2-phosphoglycerate; PEP: phosphoenolpyruvate; Pyr: pyruvate; 6PG: 6-phosphogluconate; Ru5P: ribulose 5-phosphate; R5P: ribose 5-phosphate; AcCoA: acetyl-coA; MalCoA: malonyl-coA; Cit: citrate; GLUT: glucose transporter; MCT: monocarboxylate transporter; GSH: reduced glutathione; GSSG: oxidized glutathione; H2O2: hydrogen peroxide; oxPPP: oxidative pentose phosphate pathway; TCA: tricarboxylic acid cycle; FAS: fatty acid synthesis. mTORC1 targets are omitted. See the text for details.Table 1Mitochondrial dynamics control by LKB1-AMPK.TargetRole of LKB1Biological effects(a) Role of LKB1/AMPK in mitochondrial fissionMFF (mitochondrial fission factor)AMPK-mediated phosphorylationMFF phosphorylation relocalizes the cytosolic GTPase Dynamin-Related Protein 1 (DRP1) to mitochondria, leading to mitochondrial fragmentation [138]ULK1 (Unc-51-Like Autophagy Activating Kinase 1)AMPK-mediated phosphorylationULK1 phosphorylation initiates mitophagy of damaged mitochondria, providing cancer cells with an important loophole from therapy-induced cytotoxicity [139]PGC-1α (peroxisome proliferator-activated receptor gamma coactivator 1 alpha)AMPK-mediated activationActivation of PGC-1α, the master regulator of mitochondrial biogenesis, promotes the biogenesis of new mitochondria, in order to preserve mitochondrial network functionality [139]

(b) Role of LKB1/AMPK in mitochondrial fusionMFN1 (Mitofusin-1)AMPK-mediated upregulationMFN1 mediates outer mitochondrial membrane fusion, protecting cells from mitochondrial dysfunction following a cytotoxic injury [140]OPA1 (Optic Atrophy 1)AMPK-mediated upregulationOPA1 mediates inner mitochondrial membrane fusion, protecting cells from mitochondrial dysfunction following a cytotoxic injury [140]Open in a separate windowMitochondria fusion and fission are both involved in the response of cancer cells to therapies. Several studies observed that mitochondrial fission sensitizes cancer cells to chemotherapy. Inhibition of autophagy has been shown to enhance doxorubicin cytotoxicity in breast cancer cells through mitochondrial translocation of DRP1 and consequent mitochondrial fission [64]. Similarly, LKB1-deficient NSCLC cell line A549 resulted resistant to doxorubicin-induced apoptotic cell death due to dysfunctional DRP1 that impedes mitochondrial fission [65]. Notably, AMPK promotes the maintenance of mitochondrial membrane potential following stress [66], thus preventing the proteolytic cleavage of OPA1, which is involved in cell death induction [67].In cancer cells, mitochondrial fission has also been described to trigger cell migration, leading to cell escape from stressful conditions, such as chemotherapy, metastasis, and chemoresistance. By decreasing reactive oxygen species (ROS) levels—as described later—AMPK inhibits the release of high mobility group box 1 (HMGB1), which is involved in mitochondrial fission [68], thus blunting these escape mechanisms.5. Targeting the LKB1-AMPK Pathway5.1. Activation of LKB1-AMPK Pathway by BiguanidesThe biguanide metformin attracted considerable attention as a potential anticancer drug once the connection between LKB1 and AMPK was discovered [42]. Metformin is one of the most widely used type 2 diabetes drug worldwide, and epidemiological studies revealed that diabetic patients taking metformin show a statistically significant reduced tumor incidence [69].Metformin and the related drug phenformin have been shown to inhibit complex I of the mitochondria [70], resulting in increased intracellular AMP and ADP levels, which trigger LKB1-dependent phosphorylation of AMPK [42]. Diabetic patients taking biguanides might have a lower incidence of cancer because of the role of the LKB1-AMPK pathway as a checkpoint inhibitor of cell growth and suppression of mTORC1 and other growth pathways. In addition, antitumor effects of metformin might be linked to its ability to lower circulating blood glucose and insulin levels, which also contribute to cancer risk and incidence in some contexts [69].Tumor cells lacking functional LKB1 are acutely sensitive to metabolic stress, resulting in rapid apoptosis, likely a consequence of their inability to sense energy stress and activate mechanisms to restore energy homeostasis [6]. Taking advantage of these observations, Shackelford and colleagues tested the therapeutic potential of phenformin in LKB1-deficient NSCLC experimental tumors. Phenformin as a single agent reduced tumor burden in KRAS/LKB1 comutated murine NSCLC. In particular, LKB1 inactivation renders NSCLC cells unable to modulate anabolic processes in conditions of metabolic stress caused by phenformin. The constitutive activation of KRAS pathway forced cells to duplicate their DNA and other intracellular structures, thus accelerating energy depletion and damage to intracellular components and triggering apoptosis [71].In a recent study, it has been speculated that the metabolic frailty of KRAS/LKB1 comutated NSCLC cells could be exploited pharmacologically by the combination of metformin with compounds that increase intracellular stress by interfering with DNA replication and repair, such as platinum compounds [72]. Metformin has been demonstrated to induce apoptosis in KRAS/LKB1 comutated experimental tumors. On the contrary, in KRASwt/LKB1wt cells or in the KRASmut/LKB1wt experimental tumors, metformin determined activation of the LKB1/AMPK signaling pathway, thus reducing cell proliferation and metabolic requirements and preventing metabolic crisis in cancer cells. Treatment with metformin was also associated with enhanced cisplatin-induced in vitro proapoptotic and in vivo antitumor effects specifically in KRAS/LKB1 comutated tumors [72].The opportunity to target dysregulated metabolic features in LKB1 mutated tumors could represent a strategy to improve therapeutic efficacy of other compounds affecting cell metabolism. In this regard, stable upregulation of glycolysis in tumor cells has been observed following antiangiogenic treatment [73], and as a master regulator of tumor cell metabolism and tumor microenvironment, LKB1/AMPK has a role in tumor response to VEGF neutralization [74]. Thus, sequential or simultaneous combination of antiangiogenic drugs and metformin might represent a new treatment opportunity for LKB1-deficient tumors. Although clinical and preclinical data are fragmentary, a case of a terminally ill patient with advanced endometrial cancer, showing radiological response to simultaneous administration of metformin and bevacizumab, was described by our group [75]. Interestingly, the high expression of MCT4—a marker of enhanced glycolysis—and loss of LKB1 expression were detected in the patient's liver metastasis sample. These findings suggest that metformin could modulate bevacizumab activity in tumors lacking LKB1 expression and deserves further validation in preclinical studies and clinical trials.As previously described, autophagy represents a cellular process directed to preserve cellular homeostasis. Complementary with aforementioned findings, the ability to sense and counteract different types of stresses of LKB1 proficient tumor cells might be targeted by the combination of AMPK activators, such as metformin, and autophagy inhibitors, such as chloroquine, which has been recently repurposed as an anticancer agent [76]. Speculatively, this combination, currently evaluated in clinical trials [77], should potentiate the tumor suppressor activity of LKB1-AMPK by inhibiting its oncogenic prosurvival activity.5.2. Targeting the Downstream Effectors of LKB1 Pathway5.2.1. Inhibition of mTOR Since LKB1 inactivation promotes mTORC1 signaling [46, 78] (Figure 2), mTOR inhibitors have been extensively tested as a therapeutic approach to target LKB1 mutated tumors. However, preclinical studies produced controversial results. LKB1 inactivation in endometrial cancers resulted in high responsiveness to mTOR inhibitors [79], and rapamycin monotherapy (mTORC1 inhibitor) decreased polyp burden and size in LKB1+/− mice with polyposis [62]. In contrast, LKB1 gene inactivation in NSCLC cells did not increase sensitivity to mTORC1 inhibitors, through negative feedback activation of AKT [80]. The same mechanism of escape to rapamycin could be at play in Lkb1-inactivated lung adenocarcinoma mouse model [81]. On the other hand, simultaneous inhibition of mTOR and glycolysis was significantly effective at reducing tumor volume and burden in a mouse model of spontaneous breast cancer promoted by loss of LKB1 in an ErbB2 activated model [82]. Given the master regulatory role of mTOR signaling in cell growth, additional preclinical and clinical studies are required in order to establish the appropriate genetic and molecular setting that could influence response to inhibition of mTOR pathway in the context of LKB1 status.5.2.2. Inhibition of ACC Activity

De novo FA synthesis is essential to sustain rapid tumor growth, and reprogramming of lipid metabolism is a newly recognized hallmark of malignancy. Targeting altered lipid metabolic pathways has become a promising anticancer strategy [83]. Lipid-lowering drugs are being considered for clinical trials, showing their advantages in comparison with other anticancer drugs with high toxicity [83]. Since AMPK inhibits activity of ACC [32], the rate-limiting enzyme required for de novo FA synthesis, the latter might represent a potential metabolic target in tumors lacking LKB1. Inactivation of LKB1 in the adenocarcinoma mouse model determined accumulation of lipids and low levels of FA oxidation signature genes [81]. In preclinical models, ACC was required to maintain de novo FA synthesis needed for growth and viability of NSCLC cells, and its pharmacological inhibition results in robust inhibition of tumor growth [84]. Administration of ND-646—an allosteric inhibitor of the ACC enzymes ACC1 and ACC2 that prevents ACC subunit dimerization—as a single agent or in combination with the standard-of-care drug carboplatin markedly suppressed lung tumor growth in NSCLC xenograft from LKB1-deficient cells [84]. Effects of ACC inhibition on tumor growth fit its critical role in maintaining de novo FA synthesis and prompt further investigation to define new strategies to target LKB1-defective tumors.5.3. Role of LKB1 in response to Therapy-Induced Oxidative StressROS are signaling molecules that regulate several biological processes—such as autophagy, immunity, and differentiation—through reversible thiol oxidation [85]. On the other hand, excessive ROS levels induce irreversible modification of proteins, alongside with oxidation of lipids and nucleic acids, thus leading to oxidative stress and cell death [86]. Cell fate (i.e., growth arrest, proliferation, or death) is hypothetically decided by a ROS rheostat [87], which, in cancer cells, is set to intermediate levels to sustain tumor growth. A further increase in ROS levels induces extensive damage to cell structures and selective elimination of cancer cells, implying modulation of redox homeostasis as a promising anticancer strategy [88]. Several chemotherapeutic agents and radiotherapy, indeed, kill cancer cells by increasing ROS levels beyond the toxic threshold. Cisplatin [89], paclitaxel and other taxanes [90], doxorubicin [91], cytarabine [92], and arsenic trioxide [93] are some examples of traditional drugs that induce lethal oxidative stress in cancer cells. Moreover, several mitochondria-targeting compounds, such as capsaicin [94], betulinic acid [95], and curcumin [96], induce cancer cell death by increasing ROS levels.Several studies reported that LKB1-AMPK pathway is involved in the maintenance of redox homeostasis by contrasting ROS production and promoting ROS scavenging (Figure 1). Following metabolic stress, AMPK inhibits NADPH-consuming FA synthesis and increases NADPH-producing FA oxidation, thus maintaining elevated levels of NADPH, the universal electron donor used to regenerate ROS scavenging systems, leading to cancer cell survival [35]. ROS are able to activate AMPK, which, in turn, lowers ROS levels by inducing PGC-1α-mediated antioxidant response [97]. In response to ROS, AMPK activation also promotes glycolysis and pentose phosphate pathway (PPP), thus increasing NADPH levels [98]. Recently, it has been found that the mitochondrial NADPH pool is maintained by pathways other than the PPP [99]. AMPK activates Sirtuin-3 (SIRT3), which deacetylases isocitrate dehydrogenase 2 (IDH2), one of the principal contributors to NADPH production in mitochondria, thus increasing its activity [100]. Moreover, by increasing the activity of the tricarboxylic acid cycle and FA oxidation [7], AMPK could contribute to NADPH production in mitochondria through IDH2 and malic enzymes (ME) 2 and 3. LKB1 regulates oxidative stress response through p38-mediated upregulation of mitochondrial superoxide dismutase 2 (SOD2) and catalase, which scavenge ROS [101].Given the established role of LKB1 and AMPK in maintaining redox homeostasis and the ability of ROS to kill cancer cells, one can speculate that functional LKB1-AMPK pathway could be a negative predictor of response to ROS-inducing therapies. Several evidences suggest that this is, in fact, the case.In our recent work, we observed that LKB1 loss in NSCLC cells is associated with the increased expression of NADPH oxidase 1 (NOX1), leading to elevation of ROS levels (Figure 2) and exacerbated sensitivity to exogenous oxidative stress [102]. Preliminary results by our group indicate that LKB1 deficiency is associated with increased response to several ROS-inducing drugs commonly used in the clinic, such as arsenic trioxide, paclitaxel, and doxorubicin (Figure 3), thus suggesting that LKB1 status could predict tumor response to several chemotherapeutic regimens. Moreover, we found that LKB1-defective cancer cells undergo a decrease in reduced glutathione levels following exogenous oxidative stress and are more sensitive to cisplatin and γ-irradiation, compared with LKB1-proficient cancer cells. LKB1-defective NSCLC cells exposed to exogenous oxidative stress lose their mitochondrial membrane potential and undergo mitochondrial fragmentation, while LKB1-proficient cancer cells maintained polarized and fused mitochondria [103]. These results imply that LKB1-AMPK pathway exerts a protective effect towards oxidative stress, blunting the efficacy of ROS-inducing therapies. Remarkably, low-null LKB1 expression by IHC was retrospectively associated with the improved outcome in advanced NSCLC patients treated with first-line platinum-based chemotherapy [104]. This finding may be explained by considering the well-established role of LKB1 as a genomic sensor participating in the DNA damage response triggered by oxygen radicals. Consistently, LKB1-defective cells exposed to exogenous oxidative stress showed extensive macromolecular damage, measured as membrane lipid peroxidation, accumulation of nucleic acid oxidation marker 8-oxoguanine in mitochondrial DNA, and accumulation of DNA damage marker phosphorylated histone 2AX (γH2AX). Strikingly, LKB1-defective cells demonstrated oxidation of mitochondrial DNA even under basal culture conditions, alongside with more fragmented mitochondria compared to LKB1-proficient cells. These findings support that LKB1 and AMPK protect cells from excessive oxidation of lipids and nucleic acids both by decreasing NOX-mediated ROS production and by increasing ROS scavenging, thus blunting the efficacy of anticancer therapies aimed at impairing redox homeostasis. In line with our findings, Li and colleagues observed that LKB1 loss in lung adenocarcinoma is associated with increased ROS levels, which drive cancer plasticity and drug resistance through transdifferentiation to squamous cell carcinoma in the KRAS-LKB1- (KL-) mutant lung cancer mouse model [81]. Squamous cell carcinoma, compared to adenocarcinoma, upregulated the expression of genes involved in the metabolism of glutathione and of NRF2 target genes, thus reducing DNA oxidation. Interestingly, Li and colleagues observed an inverse correlation between LKB1 expression and 8-oxoguanine levels in human NSCLC, where a proportion of cells with LKB1 loss and high 8-oxoguanine staining expressed squamous cell carcinoma markers. Reexpression of AMPK in the KL adenocarcinoma model decreased ROS levels and DNA oxidation by increasing FA oxidation-derived NADPH production, indicating the involvement of AMPK in LKB1-mediated ROS decrease, according to our findings [103]. Interestingly, Li and colleagues observed that treatment with phenformin in KL model resulted in the selective survival of squamous cell carcinoma clones and in transdifferentiation of adenocarcinoma to squamous cell carcinoma. Findings from Li and colleagues imply that LKB1 loss in adenocarcinoma could select for clones resistant to oxidative stress through increased activity of the transcription factor NRF2. Interestingly, KEAP1 is frequently inactivated in NSCLC (about 20% of cases [105]), and LKB1-defective tumors have more than sixfold increased odds of bearing KEAP1 loss compared to LKB1-proficient cancers [106]. Consequently, LKB1 loss is frequently associated with aberrant activation of NRF2 pathway, which drives aggressiveness and resistance to therapy. Constitutive NRF2 activation in cancer is connected with transcriptional programs aimed at increasing NADPH and glutathione levels, such as the serine synthesis pathway [107], which fuels mitochondrial folate cycle, the principal contributor to NADPH production in cells [99]. Thus, constitutive NRF2 activation is frequently coselected with LKB1 loss in human cancers to compensate for increased oxidative stress induced by lack of AMPK activation.Open in a separate windowFigure 3LKB1 expression regulates response to oxidative stress induced by prooxidant cytotoxic drugs. Isogenic pairs of H460 and HeLa cells (derived from NSCLC and cervical carcinoma, respectively) differing in LKB1 status and generated as described by Zulato et al. [103] were treated with arsenic trioxide, paclitaxel, or doxorubicin for 48 h. Viability was evaluated by the Sulphorhodamine B assay (for materials and methods, refer to [103]) in cells exposed to increasing concentrations of drugs. For each cell line tested, the IC50 values relative to LKB1mut and LKB1wt cells are reported. Results are representative of three independent experiments performed in triplicate (§P < 0.05, §§P < 0.01, and §§§P < 0.001 LKB1wt versus LKB1mut cells). Results of SRB assay revealed that H460 and HeLa LKB1wt variants were more resistant than their LKB1mut counterparts to the drugs tested. NE: not evaluable.5.4. Role of LKB1-AMPK in Therapy-Induced SenescenceDifferent types of stress, such as oxidative or oncogenic stresses, can induce an irreversible cell cycle arrest. Permanent blockade of cell proliferation, known as senescence, is a valuable anticancer strategy that could be achieved through sublethal chemotherapy and irradiation. High doses of chemotherapeutics or radiation cause massive damage to cell structures, leading to cell death not only in cancer cells but also in highly proliferating normal cells. On the contrary, low doses of anticancer drugs or radiation lead to therapy-induced senescence (TIS) only in cancer cells, thus decreasing side effects [108]. Noteworthily, several chemotherapeutics, including cisplatin, doxorubicin, etoposide, and resveratrol, induce senescence in cancer cells [109].Contrasting data regarding the role of AMPK on senescence induction are reported in the literature. As oxidative stress is a senescence inducer and AMPK is involved in the maintenance of redox homeostasis, it is not surprising that LKB1-AMPK pathway could prevent senescence in cancer cells [110]. Han and colleagues observed that hydrogen peroxide-induced senescence is associated with inhibition of AMPK. Furthermore, pharmacological activation of AMPK prevented the induction of senescence by oxidative stress, through restoration of autophagy. Interestingly, the authors observed that inhibition of autophagy through chloroquine aggravated senescence induced by hydrogen peroxide and blunted the protective role of AMPK activation. Moreover, NAD+ levels are decreased in senescent cells as a consequence of NAD+ salvage pathway reduction and increased NAD+ consumption by PARP-1. Pharmacological activation of AMPK promoted synthesis of NAD+ through salvage pathway, thus increasing the activity of NAD+-consumer SIRT1, which positively regulates autophagy. The results from Han and colleagues have important implications for cancer therapy. First, AMPK could have a protective role against TIS when the latter arises from a chemotherapeutic regimen that triggers oxidative stress. In this regard, metformin could increase the efficacy of chemotherapy, as described above, but could impair TIS, thus favouring the burden of surviving cells and tumor relapse. Second, autophagy emerges as an important escape mechanism from TIS, confirming its central role in the oncogenic properties of LKB1-AMPK pathway. The use of chloroquine or other inhibitors of lysosomal acidification in the clinic should enhance TIS, thus achieving remarkable anticancer activity.On the other hand, the activation of SIRT1 and AMPK has been associated with the induction of senescence in colorectal carcinoma cells [111]. Jung and colleagues observed that aspirin induced senescence in two colorectal carcinoma cell lines, but not in normal colonic cells, through the increased expression and deacetylase activity of SIRT1 and the increased activation of AMPK. The enhanced activity of SIRT1 and AMPK was induced by a decrease of ATP levels in aspirin-treated cancer cells, as observed with irradiation. Interestingly, the authors demonstrated that knockdown of SIRT1 or inhibition of its deacetylase activity decreased aspirin-induced and irradiation-induced senescence. The same results were obtained through knockdown or inhibition of AMPK. On the contrary, activation of SIRT1 through resveratrol or of AMPK through AICAR promoted the induction of senescence. The data from Jung and colleagues are consistent with the known senescence-inducing activity of resveratrol. Thus, it is reasonable that in certain cellular contexts SIRT1 and AMPK induce senescence rather than inhibit it, as observed by Han and colleagues. The decreased levels of ATP observed in aspirin-treated cells, however, suggest that in this context autophagy could not play a central role. Although aspirin induces autophagy [112], it is possible that the latter was a rescue mechanism only in the context described by Han et al., thus profoundly altering the outcome of AMPK activation. The positive role of LKB1-AMPK pathway on senescence is supported by different studies. Yi and colleagues observed that low doses of metformin induced senescence of hepatoma cells through activation of AMPK [113]. Metformin also induced the acetylation of p53 as a consequence of AMPK-mediated inhibition of SIRT1 deacetylase activity on p53. Similarly, Liao and colleagues demonstrated that AMPK activation is involved in the metabolic alterations associated with radiation-induced senescence [114].In conclusion, AMPK positively regulates TIS, implying that LKB1-proficient tumors could be more susceptible to a radiochemotherapeutic regimen that induces senescence. It should be considered, however, that AMPK-induced autophagy could be an escape mechanism that impairs TIS, thus curbing the efficacy of anticancer treatments. In this regard, a recent study provides evidence for a role of AMPK as a predictive factor of response to senescence-inducing therapies. In fact, Wang and colleagues observed that trametinib radiosensitized LKB1-defective NSCLC cells, while LKB1-proficient cells were protected by senescence through AMPK-mediated autophagy [115]. The central role of autophagy as a rescue mechanism—as recently confirmed by the observation of autophagy-mediated protumorigenic effects in the context of mitotic slippage-induced senescence [116]—suggests that the use of chloroquine in association with senescence inducers should be considered in the clinic.Interestingly, as cancer cells could recover from senescence and senescent cells secrete soluble factors that promote tumor growth [117], the use of drugs that selectively kill senescent cells (known as senolytics), such as the BCL-xL inhibitor navitoclax, in combination with senescence inducers and chloroquine should be a highly effective anticancer strategy against both LKB1-proficient and defective cancers.6. Exploiting Selective Vulnerabilities in LKB1-Defective and LKB1-Proficient TumorsA great effort focused on the identification of novel potential therapeutic targeting in highly aggressive LKB1/KRAS comutated NSCLC. Kim and colleagues tested 230,000 synthetic small molecules in a panel of 91 lung cancer-derived cell lines, identifying coatomer complex I (COPI) as necessary for the survival of LKB1/KRAS double mutant NSCLC. COPI is involved in the acidification and maturation of lysosomes, essential organelles in the maintenance of proper mitochondrial function. In fact, LKB1 inactivation and KRAS activation drive dependency on autophagy to fuel the Krebs cycle with carbon sources [118]. These interesting findings imply that autophagy inhibition through chloroquine, which blocks lysosome acidification, could be highly effective in killing LKB1/KRAS comutated NSCLC cells through the induction of mitochondrial dysfunction. Notably, although chloroquine has been tested in some studies aimed at targeting NSCLC [119–122], no reports in the literature refer to LKB1/KRAS mutations as a patient stratification criterion for the treatment of NSCLC.Deoxythymidilate kinase (DTYMK) silencing has been identified as synthetically lethal with LKB1 loss in LKB1/KRAS double mutant NSCLC [123]. DTYMK catalyses the conversion of deoxythymidine monophosphate (dTMP) to deoxythymidine diphosphate (dTDP) and plays a fundamental role in nucleotide synthesis. Liu and colleagues demonstrated that LKB1 loss is associated with deficits in nucleotide metabolism. DTYMK inhibition in LKB1-mutated NSCLC cells leads to dUTP misincorporation in DNA, thus blocking replication. As dTMP derives from folate cycle-mediated conversion of deoxyuridine monophosphate (dUMP), hypersensitivity of LKB1-mutant tumors to antifolates, such as pemetrexed, raltitrexed, or pralatrexate, can be speculated. To the best of our knowledge, therapeutic efficacy of antifolates in LKB1-mutant lung cancer has not been evaluated in patients so far.Another selective vulnerability in LKB1-mutated cancer cells is related to endoplasmic reticulum (ER) stress. Pharmacological induction of ER stress in LKB1/KRAS double mutant cancer cells triggers proapoptotic unfolded protein response and ROS-induced cell death [124]. HSP90 inhibitors and the proteasome inhibitor bortezomib are ER stress inducers currently used in the clinic. Cron and colleagues observed that proteasome inhibitors radiosensitize LKB1/KRAS double mutated NSCLC cell lines [125]. However, radiosensitization by bortezomib is a consequence of the accumulation of damaged proteins, which likely occurs independently from LKB1 status. It was observed that inactivation of LKB1 is associated with increased sensitivity to the HSP90 inhibitor 17-AAG [126–128]. Unfortunately, HSP90 chaperone protects LKB1 from proteasomal degradation [129], raising safety concerns about the exposure of normal cells to HSP90 inhibitors. Consequently, only bortezomib is a safe ER stress inducer, and more efforts should be devoted to the investigation of its efficacy in LKB1-mutated cancers.Given the role of LKB1 in the maintenance of genomic integrity through the regulation of homologous recombination, its inactivation sensitizes cancer cells to PARP inhibitors [19]. PARP-1 is involved in the repair of single-strand breaks through the base excision repair (BER) pathway [130]. Ablation of PARP leads to the conversion of single-strand breaks to double-strand breaks during DNA replication, inducing cell death in homologous recombination-defective LKB1-mutated cancer cells. PARP inhibitors are promising anticancer drugs, some of which have been approved by the Food and Drug Administration (FDA) for the treatment of BRCA-mutated cancers. The use of PARP inhibitors in LKB1-mutated human cancers holds promise of therapeutic efficacy.Some evidence suggests that LKB1 loss is involved in the upregulation of antiapoptotic proteins of the B-cell lymphoma 2 (BCL-2) family [131, 132], implying mitochondrial priming in LKB1-defective cancer. In particular, the activation of mTORC1 in LKB1-defective tumors drives the overexpression of myeloid cell leukemia 1 (MCL1) [62, 133]. In the last decade, a novel class of drugs, BH3 mimetics, was developed. BH3 mimetics mimic the structure of BH3 domain in BCL-2 family proteins, thus displacing proapoptotic BH3-only proteins from antiapoptotic proteins and inducing apoptosis. The upregulation of antiapoptotic proteins of the BCL-2 family following LKB1 loss suggests that LKB1-defective cancers could be sensitive to BH3 mimetics, particularly to MCL1 inhibitors, some of which—such as AZD5991—are currently in clinical trials for the treatment of hematological malignancies. The combination of MCL1 inhibitors with the BCL-2 specific inhibitor venetoclax should be effective against LKB1-mutated cancers and should induce a pronounced sensitization to standard chemotherapy.Additional vulnerabilities in LKB1-defective cancers are even more speculative. The increased activation of NF-κB and STAT3 pathways due to LKB1 loss could drive sensitivity to NF-κB and STAT3 inhibitors in clinical trials, such as TAS4464 and TTI-101, respectively. Inhibition of these pathways should increase mitochondrial fragmentation and sensitivity to conventional therapies.In contrast, figuring out selective vulnerabilities in LKB1-proficient cancers is not obvious. However, autophagy inhibition seems to be the most promising strategy to target drug resistance following AMPK activation, as mentioned above. In fact, the central role of ULK1 phosphorylation in the induction of angiogenesis, in the clearance of damaged mitochondria, and in maintenance of mitochondrial metabolism provides the rationale of targeting VPS34 kinase, whose activity is promoted by ULK1-mediated phosphorylation of Beclin-1. SAR405, a recently identified specific inhibitor of VPS34 kinase activity, inhibits fusion of late endosomes with lysosomes and autophagosome formation, exerting synergistic anticancer activity with the mTOR inhibitor everolimus in renal cancer cell lines [134]. Inhibition of autophagosomes leads to the accumulation of damaged and dysfunctional mitochondria, increasing the accumulation of mitochondrial ROS and inducing cell death [135]. Autophagy inhibition in LKB1-proficient tumors can be achieved with chloroquine, with some anticancer effects. However, blockade of lysosomal acidification does not impede engulfment of mitochondria in autophagosomes, which results in isolation of damaged mitochondria from the mitochondrial network. Moreover, ROS produced by damaged mitochondria inside autophagosomes must overcome two lipid membranes to reach the cytosol; thus, engulfed mitochondria release less ROS than free mitochondria.Activated AMPK phosphorylates NRF2, thus promoting its nuclear accumulation [136]. The resulting activation of an antioxidant program is responsible for the resistance to oxidative stress observed in LKB1-proficient cancers. In fact, NRF2 activates the transcription of genes involved in the production of NADPH and induces cytoprotective autophagy [137]. Speculatively, pharmacological NRF2 inhibition should revert the resistance of LKB1-proficient tumors to ROS-inducing therapies, increasing lipid peroxidation, DNA damage, loss of mitochondrial membrane potential, and mitochondrial fragmentation, ultimately leading to cell death.In conclusion, amongst several vulnerabilities affected by LKB1 status, dependency on cytoprotective autophagy and on NRF2-driven antioxidant response is shared by LKB1-proficient cancers and by LKB1-defective cancers driven by additional genetic alterations (i.e., activation of KRAS and loss of KEAP1).7. Concluding RemarksIn the era of personalized medicine, the key role of LKB1 as a central sensor of stress opens new possibilities to target cancer cell metabolism, with important clinical implications.The precise definition of LKB1 status represents a challenge for patient stratification. A comprehensive approach considering genetic, epigenetic, and LKB1 protein expression analysis should be taken into account.Cancer cell metabolism is plastic and adaptable, and LKB1 plays a central role in its modulation (Figure 1). Several evidences pointed out its contextual oncogenic and tumor suppressor role. Moreover, a key function of LKB1 in modulation of tumor microenvironment is emerging. LKB1 loss is associated with a metabolic deregulation (Figure 2) that could be exploited from a therapeutic point of view.Therefore, a better understanding of the pathways presided over by LKB1, through metabolomics and proteomics analyses, together with LKB1 status evaluation, is required to develop personalized treatment strategies. 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bitpie比特派官网|lkb

bitpie比特派官网|lkb

LKB1_百度百科

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LKB | Kastler Brossel's Laboratory - ENS - Sorbonne Université - Collège de France

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