Extracting key pathways from gene signature and genetic aberrations in subtypes of cancer

Peikai Chen, Yubo Fan, Tsz Kwong Man, Ching C. Lau, Y. S. Hung, Stephen T. Wong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Subtypes of cancer are characterized with subtype-specific aberrations and gene signature. While the gene signature is related to the consequences of the cancerous process, some of the genetic abnormalities such as copy number aberrations (CNAs) can have tumorigenic roles by perturbing various biological pathways. Bridging the gap between the aberrations and signature genes, by extracting networks that reflect the within-subtype variations, may help gain insights on the mechanisms of a cancer and its subtypes. We report a systemic approach to extract pathways. Using multivariate regression, we model the expression of a signature gene as dependent on the CNA-affected genes. The weighted ℓ1-norm penalty on the regression produces a sparse matrix, from which a bipartite graph is extracted and subtype specific networks uncovered. For each individual network, we develop an network-growing algorithm by utilizing within-subtype variations, to further identify non-signature targets. To evaluate the clinical relevance of the extracted networks, we derived a goodness-of-fit metric based on Cox proportional hazard rate model and ranked the networks based on this metric. The method was applied to two medulloblastoma datasets and the resulting networks demonstrate both dataset-invariance and biological-interpretability.

Original languageEnglish (US)
Title of host publicationComputational Intelligence Methods for Bioinformatics and Biostatistics - 9th International Meeting, CIBB 2012, Revised Selected Papers
Pages132-146
Number of pages15
DOIs
StatePublished - 2013
Event9th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2012 - Houston, TX, United States
Duration: Jul 12 2012Jul 14 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7845 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2012
CountryUnited States
CityHouston, TX
Period7/12/127/14/12

Keywords

  • ℓ- norm
  • cancer
  • copy number aberrations
  • LASSO
  • pathways
  • subtypes

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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