A Pharmacogenomic Landscape in Human Liver Cancers.
A Pharmacogenomic Landscape in Human Liver Cancers.
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人类肝癌的药物基因组学景观
DOI：
10.1016/j.ccell.2019.07.001
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发表时间：
2019-08-12
期刊：
影响因子：
50.3
通讯作者：
Hui L
中科院分区：
文献类型：
--
作者：
Qiu Z;Li H;Zhang Z;Zhu Z;He S;Wang X;Wang P;Qin J;Zhuang L;Wang W;Xie F;Gu Y;Zou K;Li C;Li C;Wang C;Cen J;Chen X;Shu Y;Zhang Z;Sun L;Min L;Fu Y;Huang X;Lv H;Zhou H;Ji Y;Zhang Z;Meng Z;Shi X;Zhang H;Li Y;Hui L
肝癌具有高度异质性，预后差，药物反应差。更好地了解基因改变和药物反应之间的关系将有助于肝癌的精确治疗。为了描述肝癌药物基因组相互作用的图景，我们开发了一种方案，以大约50%的成功率建立人肝癌细胞模型，并生成了包含81个细胞模型的肝癌模型库(LIMORE)。LIMORE代表了原发癌的基因组和转录异质性。对利莫尔药物基因组图景的询问发现了未被探索的基因-药物关联，包括对肝癌流行变化的合成致死作用。此外，预测生物标记物候选被推荐用于选择对索拉非尼有效的患者。利莫尔提供了丰富的资源，促进了肝癌的药物发现。邱等人的研究成果。建立代表东亚肝细胞癌基因组和转录异质性的肝癌模型库，结合公共和新产生的细胞系，并用它来揭示基因-药物相关性和潜在的生物标志物，用于选择索拉非尼敏感的患者。
Liver cancers are highly heterogeneous with poor prognosis and drug response. A better understanding between genetic alterations and drug responses would facilitate precision treatment for liver cancers. To characterize the landscape of pharmacogenomic interactions in liver cancers, we developed a protocol to establish human liver cancer cell models at a success rate around 50% and generated Liver Cancer Model Repository (LIMORE) with 81 cell models. LIMORE represented genomic and transcriptomic heterogeneity of primary cancers. Interrogation of the pharmacogenomic landscape of LIMORE discovered unexplored gene-drug associations, including synthetic lethalities to prevalent alterations in liver cancers. Moreover, predictive biomarker candidates were suggested for the selection of sorafenib-responding patients. LIMORE provides a rich resource facilitating drug discovery in liver cancers. Qiu et al. establish Liver Cancer Model Repository, combining public and newly-generated cell lines, that represents genomic and transcriptomic heterogeneity of Eastern Asian hepatocellular carcinomas and use it to reveal gene-drug associations and potential biomarkers for selecting sorafenib-responding patients.
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影响因子：
64.5
作者：
Basu A;Bodycombe NE;Cheah JH;Price EV;Liu K;Schaefer GI;Ebright RY;Stewart ML;Ito D;Wang S;Bracha AL;Liefeld T;Wawer M;Gilbert JC;Wilson AJ;Stransky N;Kryukov GV;Dancik V;Barretina J;Garraway LA;Hon CS;Munoz B;Bittker JA;Stockwell BR;Khabele D;Stern AM;Clemons PA;Shamji AF;Schreiber SL
通讯作者：
Schreiber SL
影响因子：
11.2
作者：
Hoshida Y;Nijman SM;Kobayashi M;Chan JA;Brunet JP;Chiang DY;Villanueva A;Newell P;Ikeda K;Hashimoto M;Watanabe G;Gabriel S;Friedman SL;Kumada H;Llovet JM;Golub TR
通讯作者：
Golub TR
影响因子：
64.5
作者：
Gao D;Vela I;Sboner A;Iaquinta PJ;Karthaus WR;Gopalan A;Dowling C;Wanjala JN;Undvall EA;Arora VK;Wongvipat J;Kossai M;Ramazanoglu S;Barboza LP;Di W;Cao Z;Zhang QF;Sirota I;Ran L;MacDonald TY;Beltran H;Mosquera JM;Touijer KA;Scardino PT;Laudone VP;Curtis KR;Rathkopf DE;Morris MJ;Danila DC;Slovin SF;Solomon SB;Eastham JA;Chi P;Carver B;Rubin MA;Scher HI;Clevers H;Sawyers CL;Chen Y
通讯作者：
Chen Y
使用下一代 DNA 测序数据进行变异发现和基因分型的框架。
影响因子：
30.8
作者：
通讯作者：
--
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.