Genomic information on tumors from 50 cancer types cataloged by the International Cancer Genome Consortium (ICGC) shows that only a few well-studied driver genes are frequently mutated, in contrast to many infrequently mutated genes that may also contribute to tumor biology. Hence there has been large interest in developing pathway and network analysis methods that group genes and illuminate the processes involved. We provide an overview of these analysis techniques and show where they guide mechanistic and translational investigations.
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We gratefully acknowledge the assistance of J. Jennings during preparation of this manuscript. J.M.S. acknowledges support from the US National Cancer Institute (R01-CA180778 and U24-CA143858), Stand Up To Cancer, the Prostate Cancer Foundation and the Movember Foundation. P.C. is currently funded by a Ludwig Fund Postdoctoral Fellowship. P.C.B. and L.D.S. were supported by the Ontario Institute for Cancer Research through funding provided by the Government of Ontario. P.C.B. was also supported by a Terry Fox Research Institute New Investigator Award and a Canadian Institutes of Health Research New Investigator Award. L.D.S. and G.W. acknowledge support from the US National Institutes of Health (NIH) and National Human Genome Research Institute (P41 HG003751). G.D.B. is supported by NRNB (NIH, National Institute of General Medical Sciences grant number P41 GM103504).
The author declare no competing financial interests.
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the Mutation Consequences and Pathway Analysis working group of the International Cancer Genome Consortium. Pathway and network analysis of cancer genomes. Nat Methods 12, 615–621 (2015). https://doi.org/10.1038/nmeth.3440
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