Combinatorial Detection of Conserved Alteration Patterns for Identifying Cancer Subnetworks

  1. Ermin Hodzic
  2. Raunak Shrestha
  3. Kaiyuan Zhu
  4. Kuoyuan Cheng
  5. Colin C Collins
  6. S Cenk Sahinalp

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

Background

Advances in large-scale tumor sequencing have led to an understanding that there are combinations of genomic and transcriptomic alterations specific to tumor types, shared across many patients. Unfortunately, computational identification of functionally meaningful and recurrent alteration patterns within gene/protein interaction networks has proven to be challenging.

Findings

We introduce a novel combinatorial method, cd-CAP (combinatorial detection of conserved alteration patterns), for simultaneous detection of connected subnetworks of an interaction network where genes exhibit conserved alteration patterns across tumor samples. Our method differentiates distinct alteration types associated with each gene (rather than relying on binary information of a gene being altered or not) and simultaneously detects multiple alteration profile conserved subnetworks.

Conclusions

In a number of The Cancer Genome Atlas datasets, cd-CAP identified large biologically significant subnetworks with conserved alteration patterns, shared across many tumor samples.

Article activity feed

  1. GigaScience

    Now published in GigaScience doi: 10.1093/gigascience/giz024

    Ermin Hodzic 1Laboratory for Advanced Genome Analysis, Vancouver Prostate Centre, Vancouver, BC, Canada2School of Computing Science, Simon Fraser University, Burnaby, BC, CanadaFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteRaunak Shrestha 1Laboratory for Advanced Genome Analysis, Vancouver Prostate Centre, Vancouver, BC, Canada3Department of Urologic Sciences, University of British Columbia, Vancouver, BC, CanadaFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteORCID record for Raunak ShresthaKaiyuan Zhu 4Department of Computer Science, Indiana University, Bloomington, IN, USAFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteKuoyuan Cheng 5Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USAFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteColin C. Collins 1Laboratory for Advanced Genome Analysis, Vancouver Prostate Centre, Vancouver, BC, Canada3Department of Urologic Sciences, University of British Columbia, Vancouver, BC, CanadaFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteS. Cenk Sahinalp 1Laboratory for Advanced Genome Analysis, Vancouver Prostate Centre, Vancouver, BC, Canada4Department of Computer Science, Indiana University, Bloomington, IN, USAFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteORCID record for S. Cenk SahinalpFor correspondence: cenksahi@indiana.edu

    A version of this preprint has been published in the Open Access journal GigaScience (see paper https://doi.org/10.1093/gigascience/giz024 ), where the paper and peer reviews are published openly under a CC-BY 4.0 license.

    These peer reviews were as follows:

    Reviewer 1: http://dx.doi.org/10.5524/REVIEW.101626 Reviewer 2: http://dx.doi.org/10.5524/REVIEW.101627

  2. Version published to 10.1093/gigascience/giz024
  3. Version published to 10.1101/369850v3 on bioRxiv
  4. Version published to 10.1101/369850v2 on bioRxiv
  5. Version published to 10.1101/369850v1 on bioRxiv