Pathway and network analysis of more than 2500 whole cancer genomes.

TitlePathway and network analysis of more than 2500 whole cancer genomes.
Publication TypeJournal Article
Year of Publication2020
AuthorsReyna, MA, Haan, D, Paczkowska, M, Verbeke, LPC, Vazquez, M, Kahraman, A, Pulido-Tamayo, S, Barenboim, J, Wadi, L, Dhingra, P, Shrestha, R, Getz, G, Lawrence, MS, Pedersen, JSkou, Rubin, MA, Wheeler, DA, Brunak, S, Izarzugaza, JMG, Khurana, E, Marchal, K, von Mering, C, S Sahinalp, C, Valencia, A, Reimand, J, Stuart, JM, Raphael, BJ
Corporate AuthorsPCAWG Drivers and Functional Interpretation Working Group, PCAWG Consortium
JournalNat Commun
Volume11
Issue1
Pagination729
Date Published2020 02 05
ISSN2041-1723
KeywordsChromatin Assembly and Disassembly, Computational Biology, Databases, Genetic, Gene Expression Regulation, Neoplastic, Genome, Human, Humans, Metabolic Networks and Pathways, Mutation, Neoplasms, Promoter Regions, Genetic, RNA Splicing
Abstract

The catalog of cancer driver mutations in protein-coding genes has greatly expanded in the past decade. However, non-coding cancer driver mutations are less well-characterized and only a handful of recurrent non-coding mutations, most notably TERT promoter mutations, have been reported. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancer across 38 tumor types, we perform multi-faceted pathway and network analyses of non-coding mutations across 2583 whole cancer genomes from 27 tumor types compiled by the ICGC/TCGA PCAWG project that was motivated by the success of pathway and network analyses in prioritizing rare mutations in protein-coding genes. While few non-coding genomic elements are recurrently mutated in this cohort, we identify 93 genes harboring non-coding mutations that cluster into several modules of interacting proteins. Among these are promoter mutations associated with reduced mRNA expression in TP53, TLE4, and TCF4. We find that biological processes had variable proportions of coding and non-coding mutations, with chromatin remodeling and proliferation pathways altered primarily by coding mutations, while developmental pathways, including Wnt and Notch, altered by both coding and non-coding mutations. RNA splicing is primarily altered by non-coding mutations in this cohort, and samples containing non-coding mutations in well-known RNA splicing factors exhibit similar gene expression signatures as samples with coding mutations in these genes. These analyses contribute a new repertoire of possible cancer genes and mechanisms that are altered by non-coding mutations and offer insights into additional cancer vulnerabilities that can be investigated for potential therapeutic treatments.

DOI10.1038/s41467-020-14367-0
Alternate JournalNat Commun
PubMed ID32024854
PubMed Central IDPMC7002574
Grant ListU01 CA217875 / CA / NCI NIH HHS / United States
P30 CA008748 / CA / NCI NIH HHS / United States
R01 CA218668 / CA / NCI NIH HHS / United States
T32 GM008313 / GM / NIGMS NIH HHS / United States
U24 CA210990 / CA / NCI NIH HHS / United States
U24 CA211000 / CA / NCI NIH HHS / United States
P30 CA016672 / CA / NCI NIH HHS / United States
R01 GM109031 / GM / NIGMS NIH HHS / United States
R01 HG007069 / HG / NHGRI NIH HHS / United States