Liver cancers are highly heterogeneous with poor prognosis and low drug response rate. A better understanding between genetic alterations and drug responses would facilitate precision treatment for liver cancers. To largely characterize the landscape of pharmacogenomic interactions in liver cancers, we developed Liver Cancer Model Repository (LIMORE) composed of 81 human liver cancer cell models, including 50 newly generated models.
LIMORE largely retained genomic and transcriptomic features of primary liver cancers. Interrogation of the pharmacogenomic landscape from a high-throughput drug screening discovered unexplored gene-drug associations, including novel synthetic lethal strategies to prevalent alterations, in liver cancers. Morevoer, predictive biomarkers and models were developed to facilitate the selection of sorafenib-responding patients. In total, LIMORE platform provides a rich resource of preclinical models and datasets to expand our knowledge and facilitate drug development in liver cancers.
19.04.01 UPDATES
------- Representative pictures of patient HE, xenograft HE and cell lines.
------- Gene-drug interactions from pharmacogenomics analysis.
18.09.25 UPDATES
------- Registration of 5 new liver cancer cell lines.
------- WGS/RNA-Seq data of 81 liver cancer cell lines.
------- Drug sensitivity data for 90 drugs in 81 liver cancer cell lines.
17.05.01 v1 dataset released:
------- Registration of 77 liver cancer cell lines.
------- A subset of 66 cell lines: The information includes DNA/RNA sequencing results (Whole genome/exome sequencing and RNA-Seq) and related patients’ clinical information.
------- Caution! SK-HEP1 cell line was reported to be endothelial origin.
- Qiu et al., A Pharmacogenomic Landscape in Human Liver Cancers, Cancer Cell (2019), https://doi.org/10.1016/j.ccell.2019.07.001. Pubmed ID: 31378681
- Qiu, Z.*, Zou, K.*, Zhuang, L.*, Qin, J.*, Li, H., Li, C., Zhang, Z., Chen, X., Cen, J., Meng, Z., Zhang, H., Li, Y., and Hui, L. (2016) Hepatocellular carcinoma cell lines retain the genomic and transcriptomic landscapes of primary human cancers. Scientific reports 6, 27411. (one of the top 100 read SR articles in 2016). doi:10.1038/srep27411. Pubmed ID: 27273737