Identification of novel prostate cancer drivers using RegNetDriver: a framework for integration of genetic and epigenetic alterations with tissue-specific regulatory network. Academic Article uri icon

Overview

abstract

  • We report a novel computational method, RegNetDriver, to identify tumorigenic drivers using the combined effects of coding and non-coding single nucleotide variants, structural variants, and DNA methylation changes in the DNase I hypersensitivity based regulatory network. Integration of multi-omics data from 521 prostate tumor samples indicated a stronger regulatory impact of structural variants, as they affect more transcription factor hubs in the tissue-specific network. Moreover, crosstalk between transcription factor hub expression modulated by structural variants and methylation levels likely leads to the differential expression of target genes. We report known prostate tumor regulatory drivers and nominate novel transcription factors (ERF, CREB3L1, and POU2F2), which are supported by functional validation.

publication date

  • July 27, 2017

Research

keywords

  • Algorithms
  • Carcinogenesis
  • Cyclic AMP Response Element-Binding Protein
  • Gene Expression Regulation, Neoplastic
  • Nerve Tissue Proteins
  • Octamer Transcription Factor-2
  • Prostatic Neoplasms
  • Repressor Proteins

Identity

PubMed Central ID

  • PMC5530464

Scopus Document Identifier

  • 85026383892

Digital Object Identifier (DOI)

  • 10.1093/jnci/djn150

PubMed ID

  • 28750683

Additional Document Info

volume

  • 18

issue

  • 1