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Nat Genet. 2018 Apr;50(4):613-620. doi: 10.1038/s41588-018-0091-2. Epub 2018 Apr 2.

A global transcriptional network connecting noncoding mutations to changes in tumor gene expression.

Author information

1
Department of Medicine, University of California, San Diego, La Jolla, CA, USA. wez124@ucsd.edu.
2
Department of Medicine, University of California, San Diego, La Jolla, CA, USA.
3
Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA.
4
Center for Computational Biology and Bioinformatics, University of California, San Diego, La Jolla, CA, USA.
5
Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
6
Division of Biological Sciences, University of California, San Diego, La Jolla, CA, USA.
7
Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA.
8
Department of Medicine, University of California, San Diego, La Jolla, CA, USA. jkreisberg@ucsd.edu.
9
Department of Medicine, University of California, San Diego, La Jolla, CA, USA. tideker@ucsd.edu.
10
Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA. tideker@ucsd.edu.
11
Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA. tideker@ucsd.edu.
12
Cancer Cell Map Initiative (CCMI), University ofCalifornia, La Jolla and San Francisco, CA, USA. tideker@ucsd.edu.

Abstract

Although cancer genomes are replete with noncoding mutations, the effects of these mutations remain poorly characterized. Here we perform an integrative analysis of 930 tumor whole genomes and matched transcriptomes, identifying a network of 193 noncoding loci in which mutations disrupt target gene expression. These 'somatic eQTLs' (expression quantitative trait loci) are frequently mutated in specific cancer tissues, and the majority can be validated in an independent cohort of 3,382 tumors. Among these, we find that the effects of noncoding mutations on DAAM1, MTG2 and HYI transcription are recapitulated in multiple cancer cell lines and that increasing DAAM1 expression leads to invasive cell migration. Collectively, the noncoding loci converge on a set of core pathways, permitting a classification of tumors into pathway-based subtypes. The somatic eQTL network is disrupted in 88% of tumors, suggesting widespread impact of noncoding mutations in cancer.

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