Network perturbation by recurrent regulatory variants in cancer

PLoS Comput Biol. 2017 Mar 23;13(3):e1005449. doi: 10.1371/journal.pcbi.1005449. eCollection 2017 Mar.

Abstract

Cancer driving genes have been identified as recurrently affected by variants that alter protein-coding sequences. However, a majority of cancer variants arise in noncoding regions, and some of them are thought to play a critical role through transcriptional perturbation. Here we identified putative transcriptional driver genes based on combinatorial variant recurrence in cis-regulatory regions. The identified genes showed high connectivity in the cancer type-specific transcription regulatory network, with high outdegree and many downstream genes, highlighting their causative role during tumorigenesis. In the protein interactome, the identified transcriptional drivers were not as highly connected as coding driver genes but appeared to form a network module centered on the coding drivers. The coding and regulatory variants associated via these interactions between the coding and transcriptional drivers showed exclusive and complementary occurrence patterns across tumor samples. Transcriptional cancer drivers may act through an extensive perturbation of the regulatory network and by altering protein network modules through interactions with coding driver genes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Computer Simulation
  • Gene Expression Regulation, Neoplastic / genetics*
  • Genes, Neoplasm / genetics*
  • Genetic Variation / genetics
  • Humans
  • Models, Genetic*
  • Neoplasm Proteins / genetics
  • Neoplasms / genetics*
  • Regulatory Elements, Transcriptional / genetics*
  • Signal Transduction / genetics*

Substances

  • Neoplasm Proteins

Grants and funding

This work was supported by the “Development of biomedical data network analysis technology based on high performance computing for dementia researches (K-16-L03-C02-S02)” funded by KISTI, and by a grant from the Korea Healthcare Technology R&D Project, Ministry for Health & Welfare Affairs (HI13C0715). Research facilities were supported by the CHUNG Moon Soul Center of KAIST and by the Data Computing Project of KISTI-GSDC. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.