| Literature DB >> 31378681 |
Zhixin Qiu1, Hong Li2, Zhengtao Zhang1, Zhenfeng Zhu3, Sheng He4, Xujun Wang5, Pengcheng Wang6, Jianjie Qin7, Liping Zhuang3, Wei Wang8, Fubo Xie8, Ying Gu8, Keke Zou2, Chao Li2, Chun Li1, Chenhua Wang1, Jin Cen1, Xiaotao Chen1, Yajing Shu1, Zhao Zhang1, Lulu Sun1, Lihua Min1, Yong Fu9, Xiaowu Huang6, Hui Lv5, He Zhou8, Yuan Ji10, Zhigang Zhang11, Zhiqiang Meng3, Xiaolei Shi12, Haibin Zhang13, Yixue Li14, Lijian Hui15.
Abstract
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 of around 50% and generated the 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.Entities:
Keywords: liver cancer; patient-derived cancer models; pharmacogenomics; sorafenib
Year: 2019 PMID： 31378681 DOI： 10.1016/j.ccell.2019.07.001
Source DB: PubMed Journal: Cancer Cell ISSN： 1535-6108 Impact factor: 31.743