Common and cell-type specific responses to anti-cancer drugs revealed by high throughput transcript profiling.
Common and cell-type specific responses to anti-cancer drugs revealed by high throughput transcript profiling.
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DOI：
10.1038/s41467-017-01383-w
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发表时间：
2017-10-30
影响因子：
16.6
通讯作者：
Sorger PK
中科院分区：
文献类型：
--
作者：
Niepel M;Hafner M;Duan Q;Wang Z;Paull EO;Chung M;Lu X;Stuart JM;Golub TR;Subramanian A;Ma'ayan A;Sorger PK
更有效地使用靶向抗癌药物取决于阐明药物治疗诱导的分子状态与这些状态控制的细胞表型（如细胞停滞和死亡）之间的联系。当单个基因的突变不足以预测药物反应时，情况尤其如此。本文描述了作为NIH LINCS计划（http：//www.lincsproject.org/）的一部分收集的约600个药物细胞系对的数据集，其中记录了不同剂量和时间的分子数据（降维转录本L1000谱），同时记录了细胞细胞抑制和细胞毒性的表型数据。我们报告说，转录和表型反应相互关联的一般情况下，但而伴侣蛋白和细胞周期激酶的抑制剂诱导类似的转录变化跨细胞系，细胞内信号转导激酶抑制药物诱导的变化是细胞类型特异性的。在一些药物/细胞系对中，观察到转录的显著变化，而细胞生长或存活没有变化;对这些对的分析鉴定了药物等效性类别，并且在一种情况下，鉴定了协同药物相互作用。在这种情况下，协同作用涉及适应性药物反应的细胞类型特异性抑制。了解为什么一些肿瘤细胞对治疗有反应，而另一些则没有反应，对于推进精确的癌症治疗至关重要。在这里，作者对用抗癌药物治疗的乳腺癌细胞系进行了大规模的转录组学分析，发现某些药物类别诱导细胞系特异性反应。
More effective use of targeted anti-cancer drugs depends on elucidating the connection between the molecular states induced by drug treatment and the cellular phenotypes controlled by these states, such as cytostasis and death. This is particularly true when mutation of a single gene is inadequate as a predictor of drug response. The current paper describes a data set of ~600 drug cell line pairs collected as part of the NIH LINCS Program (http://www.lincsproject.org/) in which molecular data (reduced dimensionality transcript L1000 profiles) were recorded across dose and time in parallel with phenotypic data on cellular cytostasis and cytotoxicity. We report that transcriptional and phenotypic responses correlate with each other in general, but whereas inhibitors of chaperones and cell cycle kinases induce similar transcriptional changes across cell lines, changes induced by drugs that inhibit intra-cellular signaling kinases are cell-type specific. In some drug/cell line pairs significant changes in transcription are observed without a change in cell growth or survival; analysis of such pairs identifies drug equivalence classes and, in one case, synergistic drug interactions. In this case, synergy involves cell-type specific suppression of an adaptive drug response. Understanding why some tumor cells respond to therapy and others do not is essential for advancing precision cancer care. Here, the authors perform large-scale transcriptomic profiling of breast cancer cell lines treated with anti-cancer drugs and find that certain drug classes induce cell line specific responses.
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影响因子：
64.5
作者：
Brunet, A;Bonni, A;Greenberg, ME
通讯作者：
Greenberg, ME
影响因子：
3
作者：
Clark NR;Hu KS;Feldmann AS;Kou Y;Chen EY;Duan Q;Ma'ayan A
通讯作者：
Ma'ayan A
DOI：
10.1136/amiajnl-2013-002512
发表时间：
2014-10-01
影响因子：
6.4
作者：
Cheng, Feixiong;Zhao, Zhongming
通讯作者：
Zhao, Zhongming
影响因子：
64.8
作者：
Garnett, Mathew J.;Edelman, Elena J.;Heidorn, Sonja J.;Greenman, Chris D.;Dastur, Anahita;Lau, King Wai;Greninger, Patricia;Thompson, I. Richard;Luo, Xi;Soares, Jorge;Liu, Qingsong;Iorio, Francesco;Surdez, Didier;Chen, Li;Milano, Randy J.;Bignell, Graham R.;Tam, Ah T.;Davies, Helen;Stevenson, Jesse A.;Barthorpe, Syd;Lutz, Stephen R.;Kogera, Fiona;Lawrence, Karl;McLaren-Douglas, Anne;Mitropoulos, Xeni;Mironenko, Tatiana;Thi, Helen;Richardson, Laura;Zhou, Wenjun;Jewitt, Frances;Zhang, Tinghu;O'Brien, Patrick;Boisvert, Jessica L.;Price, Stacey;Hur, Wooyoung;Yang, Wanjuan;Deng, Xianming;Butler, Adam;Choi, Hwan Geun;Chang, JaeWon;Baselga, Jose;Stamenkovic, Ivan;Engelman, Jeffrey A.;Sharma, Sreenath V.;Delattre, Olivier;Saez-Rodriguez, Julio;Gray, Nathanael S.;Settleman, Jeffrey;Futreal, P. Andrew;Haber, Daniel A.;Stratton, Michael R.;Ramaswamy, Sridhar;McDermott, Ultan;Benes, Cyril H.
通讯作者：
Benes, Cyril H.
影响因子：
64.5
作者：
Ciriello G;Gatza ML;Beck AH;Wilkerson MD;Rhie SK;Pastore A;Zhang H;McLellan M;Yau C;Kandoth C;Bowlby R;Shen H;Hayat S;Fieldhouse R;Lester SC;Tse GM;Factor RE;Collins LC;Allison KH;Chen YY;Jensen K;Johnson NB;Oesterreich S;Mills GB;Cherniack AD;Robertson G;Benz C;Sander C;Laird PW;Hoadley KA;King TA;TCGA Research Network;Perou CM
通讯作者：
Perou CM