A Landscape of Pharmacogenomic Interactions in Cancer.
A Landscape of Pharmacogenomic Interactions in Cancer.
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DOI：
10.1016/j.cell.2016.06.017
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发表时间：
2016-07-28
期刊：
影响因子：
64.5
通讯作者：
Garnett MJ
中科院分区：
文献类型：
--
作者：
Iorio F;Knijnenburg TA;Vis DJ;Bignell GR;Menden MP;Schubert M;Aben N;Gonçalves E;Barthorpe S;Lightfoot H;Cokelaer T;Greninger P;van Dyk E;Chang H;de Silva H;Heyn H;Deng X;Egan RK;Liu Q;Mironenko T;Mitropoulos X;Richardson L;Wang J;Zhang T;Moran S;Sayols S;Soleimani M;Tamborero D;Lopez-Bigas N;Ross-Macdonald P;Esteller M;Gray NS;Haber DA;Stratton MR;Benes CH;Wessels LFA;Saez-Rodriguez J;McDermott U;Garnett MJ
癌症基因组的系统研究为癌症的分子性质提供了前所未有的见解。使用这些信息来指导临床疗法的开发和应用具有挑战性。在这里，我们报告了如何将来自 29 个组织的 11,289 个肿瘤中发现的癌症驱动的改变（整合体细胞突变、拷贝数改变、DNA 甲基化和基因表达）映射到 1,001 个分子注释的人类癌细胞系上，并与对 265 种药物的敏感性相关联。我们发现细胞系忠实地再现了肿瘤中发现的致癌改变，发现其中许多与药物敏感性/耐药性相关，并强调了组织谱系在介导药物反应中的重要性。基于逻辑的建模揭示了对药物敏感的改变组合，而机器学习则证明了不同数据类型在预测药物反应中的相对重要性。我们的分析和数据集是丰富的资源，可将基因型与细胞表型联系起来，并为选定的癌症亚群确定治疗方案。我们整合了 11,289 个肿瘤和 1,001 个细胞系的异质分子数据 我们测量了 1,001 个癌细胞系对 265 种抗癌药物的反应 我们发现了许多对抗癌药物敏感的致癌畸变 我们的研究形成了确定癌症亚群治疗方案的资源 对 1,001 个人类癌细胞系的药物基因组景观的观察指出了数百种已知抗癌药物的新治疗应用。
Systematic studies of cancer genomes have provided unprecedented insights into the molecular nature of cancer. Using this information to guide the development and application of therapies in the clinic is challenging. Here, we report how cancer-driven alterations identified in 11,289 tumors from 29 tissues (integrating somatic mutations, copy number alterations, DNA methylation, and gene expression) can be mapped onto 1,001 molecularly annotated human cancer cell lines and correlated with sensitivity to 265 drugs. We find that cell lines faithfully recapitulate oncogenic alterations identified in tumors, find that many of these associate with drug sensitivity/resistance, and highlight the importance of tissue lineage in mediating drug response. Logic-based modeling uncovers combinations of alterations that sensitize to drugs, while machine learning demonstrates the relative importance of different data types in predicting drug response. Our analysis and datasets are rich resources to link genotypes with cellular phenotypes and to identify therapeutic options for selected cancer sub-populations. We integrate heterogeneous molecular data of 11,289 tumors and 1,001 cell lines We measure the response of 1,001 cancer cell lines to 265 anti-cancer drugs We uncover numerous oncogenic aberrations that sensitize to an anti-cancer drug Our study forms a resource to identify therapeutic options for cancer sub-populations A look at the pharmacogenomic landscape of 1,001 human cancer cell lines points to new treatment applications for hundreds of known anti-cancer drugs.