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A comprehensive transcriptional portrait of human cancer cell lines

Nature Biotechnology volume 33, pages 306–312 (2015)Cite this article

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Abstract

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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Figure 1: Data set overview.
Figure 2: Detection of gene fusion events in human cell lines.
Figure 3: Pathway-based mutation aggregation shows tissue-specific pathway deregulation.
Figure 4: Pathway aggregation of cell line aberrations.

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ArrayExpress

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Gene Expression Omnibus

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Acknowledgements

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.

Author information

Authors and Affiliations

  1. Department of Bioinformatics and Computational Biology, Genentech Inc., South San Francisco, California, USA

    Christiaan Klijn, Steffen Durinck, Eric W Stawiski, Peter M Haverty, Zhaoshi Jiang, Hanbin Liu, Jeremiah Degenhardt, Oleg Mayba, Florian Gnad, Jinfeng Liu, Gregoire Pau, Jens Reeder, Yi Cao, Kiran Mukhyala, Gregory J Zynda, Matthew J Brauer, Thomas D Wu, Robert C Gentleman, Gerard Manning, Richard Bourgon & Zemin Zhang

  2. Department of Molecular Biology, Genentech Inc., South San Francisco, California, USA

    Steffen Durinck, Eric W Stawiski, Zora Modrusan, Frederic J de Sauvage & Somasekar Seshagiri

  3. Department of Discovery Oncology, Genentech Inc., South San Francisco, California, USA

    Yi Cao, Suresh K Selvaraj, Mamie Yu, Robert L Yauch, David Stokoe, Richard M Neve & Jeffrey Settleman

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  1. Christiaan Klijn
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Contributions

C.K., F.J.d.S., J.S., S.S. and Z.Z. conceived the project. C.K., J.S., S.S. and Z.Z. wrote the manuscript. C.K., S.D., E.W.S., P.M.H., Z.J., H.L., J.D., O.M., F.G., J.L., G.P., J.R., K.M., G.J.Z., M.J.B., T.D.W., R.C.G., G.M. and R.B. performed bioinformatics data analysis or provided computational infrastructure. Y.C., S.K.S., M.Y., R.L.Y., D.S., Z.M. and R.M.N. prepared cell lines and performed biochemical experiments including drug treatments and sequencing.

Corresponding authors

Correspondence to Jeffrey Settleman, Somasekar Seshagiri or Zemin Zhang.

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Competing interests

The majority of authors are employees of Genentech Inc. and/or hold stock in Roche.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–18, Supplementary Tables 3, 5, 9 and 12 and Supplementary Note (PDF 23603 kb)

Supplementary Table 1

Overview of cell lines included in this study (XLS 203 kb)

Supplementary Table 2

Sequencing statistics for RNA sequencing of cancer cell lines (XLS 126 kb)

Supplementary Table 4

Results for GISTIC analysis run on 610 cell lines (XLS 71 kb)

Supplementary Table 6

Viral integration sites detected by human-viral chimeric RNA (XLS 53 kb)

Supplementary Table 7

Viral integration sites detected by human-viral chimeric RNA - murine viruses (XLS 77 kb)

Supplementary Table 8

Gene-gene fusions identified in cancer cell lines (XLS 1397 kb)

Supplementary Table 10

Fusions found in TCGA for which at least one gene was also found in a fusion in cell lines (XLS 2035 kb)

Supplementary Table 11

Crizotinib response in cancer cell lines (XLS 149 kb)

Supplementary Table 13

IC50 values for five drugs determined in 351 cell lines (XLS 80 kb)

Supplementary Data 1

Gene expression read counts for all coding genes (ZIP 104720 kb)

Supplementary Data 2

Gene expression read counts for all non-coding genes (ZIP 49333 kb)

Supplementary Data 3

All single nucleotide mutations found in cell lines in this study. (ZIP 20500 kb)

Supplementary Data 4

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://doi.org/10.1038/nbt.3080

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