Tumor-derived cell lines have served as vital models to advance our understanding of oncogene function and therapeutic responses. Although substantial effort has been made to define the genomic constitution of cancer cell line panels, the transcriptome remains understudied. Here we describe RNA sequencing and single-nucleotide polymorphism (SNP) array analysis of 675 human cancer cell lines. We report comprehensive analyses of transcriptome features including gene expression, mutations, gene fusions and expression of non-human sequences. Of the 2,200 gene fusions catalogued, 1,435 consist of genes not previously found in fusions, providing many leads for further investigation. We combine multiple genome and transcriptome features in a pathway-based approach to enhance prediction of response to targeted therapeutics. Our results provide a valuable resource for studies that use cancer cell lines.
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We thank members of the Genentech cell line bank (gCell) and the compound screening group (gCSI) for contributing cell lines and results to this paper. We thank A. Bruce for graphical assistance.
The majority of authors are employees of Genentech Inc. and/or hold stock in Roche.
Supplementary Figures 1–18, Supplementary Tables 3, 5, 9 and 12 and Supplementary Note (PDF 23603 kb)
Overview of cell lines included in this study (XLS 203 kb)
Sequencing statistics for RNA sequencing of cancer cell lines (XLS 126 kb)
Results for GISTIC analysis run on 610 cell lines (XLS 71 kb)
Viral integration sites detected by human-viral chimeric RNA (XLS 53 kb)
Viral integration sites detected by human-viral chimeric RNA - murine viruses (XLS 77 kb)
Gene-gene fusions identified in cancer cell lines (XLS 1397 kb)
Fusions found in TCGA for which at least one gene was also found in a fusion in cell lines (XLS 2035 kb)
Crizotinib response in cancer cell lines (XLS 149 kb)
IC50 values for five drugs determined in 351 cell lines (XLS 80 kb)
Gene expression read counts for all coding genes (ZIP 104720 kb)
Gene expression read counts for all non-coding genes (ZIP 49333 kb)
All single nucleotide mutations found in cell lines in this study. (ZIP 20500 kb)
Per-gene ploidy-corrected copy number values (ZIP 7901 kb)
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Klijn, C., Durinck, S., Stawiski, E. et al. A comprehensive transcriptional portrait of human cancer cell lines. Nat Biotechnol 33, 306–312 (2015). https://xs.scihub.ltd/https://doi.org/10.1038/nbt.3080
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