Pan-cancer RNA-seq data stratifies tumours by some hallmarks of cancer.

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We hypothesized that RNA-Seq identifies gene expression changes that underly those hallmarks, and thereby defines relevant therapeutic targets. To test this hypothesis, we analysed the publicly available TCGA-TARGET-GTEx gene expression data set from the University of California Santa CruzToil recompute project using WGCNA to delineate co-correlated 'modules' from tumour gene expression profiles and functional enrichment of these modules to hierarchically cluster tumours. This stratified tumours according to T cell activation, NK-cell activation, complement cascade, ATM, Rb, angiogenic, MAPK, ECM receptor and histone modification signalling. These correspond to the cancer hallmarks of avoiding immune destruction, tumour-promoting inflammation, evading growth suppressors, inducing angiogenesis, sustained proliferative signalling, activating invasion and metastasis, and genome instability and mutation. This approach did not detect pathways corresponding to the cancer enabling replicative immortality, resisting cell death or deregulating cellular energetics hallmarks. We conclude that RNA-Seq stratifies tumours along some, but not all, hallmarks of cancer and, therefore, could be used in conjunction with other analyses collectively to inform precision therapy.", "claims": [{"id": "claim-method", "statement": "Each data set was analysed using WGCNA to identify groups of genes (modules) that were co‐correlated, and variable across cancers (C).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31730267", "locator": "sections[3] \"Data sources and processing\" paragraph 4", "quote": "Each data set was analysed using WGCNA to identify groups of genes (modules) that were co‐correlated, and variable across cancers (C)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data used in this study is freely available from the UCSC Xena Data Browser. 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