Transcriptome Profiling of Acquired Gefitinib Resistant Lung Cancer Cells Reveals Dramatically Changed Transcription Programs and New Treatment Targets
Transcriptome Profiling of Acquired Gefitinib Resistant Lung Cancer Cells Reveals Dramatically Changed Transcription Programs and New Treatment Targets
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获得性吉非替尼耐药肺癌细胞的转录组分析揭示了转录程序的巨大变化和新的治疗靶点
DOI：
10.3389/fonc.2020.01424
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发表时间：
2020-08
期刊：
影响因子：
--
通讯作者：
Zhangxiao Ju
中科院分区：
文献类型：
--
作者：
Nan Wei;Yong'an Song;Fan Zhang;Zhifu Sun;Zhangxiao Ju
背景资料：用酪氨酸激酶抑制剂（TKI）靶向治疗表皮生长因子受体（EGFR）突变的肺癌是肺癌治疗的重大突破之一。然而，对这些药物逐渐产生的耐药性阻碍了持续的临床益处，并要求进行耐药机制研究和鉴定新的治疗靶点。获得性T790 M突变占大多数耐药病例，但这些细胞中的转录组变化特征较少，并且尚不清楚现有药物是否存在新的治疗靶点。研究方法：通过RNA测序对肺癌细胞系PC 9及其耐药细胞系PC 9 GR长期暴露于吉非替尼后进行转录组分析。沿着现有的靶向这些上调基因的药物，鉴定了差异表达的基因和改变的途径。使用来自癌细胞系百科全书（CCLE）和癌症治疗反应门户（CTRP）的基因表达和药物反应数据的144种肺癌细胞系，我们筛选了549种药物，其反应与PC 9 GR细胞中这些上调的基因相关，并评估了顶级药物在PC 9和PC 9 GR细胞中的反应。结果：耐药PC 9 GR细胞除了存在获得性T790 M突变外，还存在与敏感PC 9细胞不同的转录程序。多个通路发生变化，其中最重要的通路包括TNFA信号传导、雄激素/雌激素反应、P53通路、MTORC 1信号传导、缺氧和上皮间质转化。32个上调的基因有可能有效治疗耐药细胞的药物。从CCLE的反应谱中，我们发现了17种药物，其反应与至少四种这些上调基因相关。在评价的四种药物（达沙替尼、KPT-185、曲美替尼和普卢立泊汀）中，除曲美替尼外，所有药物均对耐药PC 9 GR细胞表现出强抑制作用，其中KPT-185最有效。KPT-185以剂量依赖性方式抑制生长，引起细胞凋亡，并以与敏感的PC 9细胞相似（或更好）的速率抑制PC 9 GR细胞的迁移。结论：获得性TKI耐药肺癌细胞（PC 9 GR）显著改变了转录和通路调控，从而暴露了新的治疗靶点。现有的药物可能被重新用于治疗对TKI产生耐药性的患者。
Background: Targeted therapy for lung cancer with epidermal growth factor receptor (EGFR) mutations with tyrosine kinase inhibitors (TKIs) represents one of the major breakthroughs in lung cancer management. However, gradually developed resistance to these drugs prevents sustained clinical benefits and calls for resistant mechanism research and identification of new therapeutic targets. Acquired T790M mutation accounts for the majority of resistance cases, yet transcriptome changes in these cells are less characterized, and it is not known if new treatment targets exist by available drugs. Methods: Transcriptome profiling was performed for lung cancer cell line PC9 and its resistant line PC9GR after long-term exposure to gefitinib through RNA sequencing. Differentially expressed genes and changed pathways were identified along with existing drugs targeting these upregulated genes. Using 144 lung cancer cell lines with both gene expression and drug response data from the cancer cell line encyclopedia (CCLE) and Cancer Therapeutics Response Portal (CTRP), we screened 549 drugs whose response was correlated with these upregulated genes in PC9GR cells, and top drugs were evaluated for their response in both PC9 and PC9GR cells. Results: In addition to the acquired T790M mutation, the resistant PC9GR cells had very different transcription programs from the sensitive PC9 cells. Multiple pathways were changed with the top ones including TNFA signaling, androgen/estrogen response, P53 pathway, MTORC1 signaling, hypoxia, and epithelial mesenchymal transition. Thirty-two upregulated genes had available drugs that can potentially be effective in treating the resistant cells. From the response profiles of CCLE, we found 17 drugs whose responses were associated with at least four of these upregulated genes. Among the four drugs evaluated (dasatinib, KPT-185, trametinib, and pluripotin), all except trametinib demonstrated strong inhibitory effects on the resistant PC9GR cells, among which KPT185 was the most potent. KPT-185 suppressed growth, caused apoptosis, and inhibited migration of the PC9GR cells at similar (or better) rates as the sensitive PC9 cells in a dose-dependent manner. Conclusions: Acquired TKI-resistant lung cancer cells (PC9GR) have dramatically changed transcription and pathway regulation, which expose new treatment targets. Existing drugs may be repurposed to treat those patients with developed resistance to TKIs.
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DOI：
10.1016/b978-0-12-809633-8.20106-4
发表时间：
2020-02
期刊：
--
影响因子：
--
作者：
A. Prjibelski;Anton I. Korobeynikov;Alla L. Lapidus
通讯作者：
A. Prjibelski;Anton I. Korobeynikov;Alla L. Lapidus
DOI：
10.1101/275974
发表时间：
2018-03
期刊：
bioRxiv
影响因子：
--
作者：
P. Fan;G. Narzisi;A. Jayaprakash;E. Venturini;N. Robine;Peter Smibert;S. Germer;H. Yu;E. Jordan;P. Paik;Y. Janjigian;J. Chaft;Lu Wang;A. Jungbluth;S. Middha;L. Spraggon;H. Qiao;C. Lovly;M. Kris;Gregory Riely;K. Politi;H. Varmus;M. Ladanyi
通讯作者：
P. Fan;G. Narzisi;A. Jayaprakash;E. Venturini;N. Robine;Peter Smibert;S. Germer;H. Yu;E. Jordan;P. Paik;Y. Janjigian;J. Chaft;Lu Wang;A. Jungbluth;S. Middha;L. Spraggon;H. Qiao;C. Lovly;M. Kris;Gregory Riely;K. Politi;H. Varmus;M. Ladanyi
影响因子：
28.2
作者：
Takezawa K;Pirazzoli V;Arcila ME;Nebhan CA;Song X;de Stanchina E;Ohashi K;Janjigian YY;Spitzler PJ;Melnick MA;Riely GJ;Kris MG;Miller VA;Ladanyi M;Politi K;Pao W
通讯作者：
Pao W
影响因子：
3.7
作者：
Fukuoka M;Yoshioka K;Hohjoh H
通讯作者：
Hohjoh H
影响因子：
14.9
作者：
Ritchie ME;Phipson B;Wu D;Hu Y;Law CW;Shi W;Smyth GK
通讯作者：
Smyth GK