Breast cancer biomarker discovery in the functional genomic age: A systematic review of 42 gene expression signatures

M. C. Abba, E. Lacunza, M. Butti, C. M. Aldaz

Research output: Contribution to journalReview articlepeer-review

41 Scopus citations

Abstract

In this review we provide a systematic analysis of transcriptomic signatures derived from 42 breast cancer gene expression studies, in an effort to identify the most relevant breast cancer biomarkers using a meta-analysis method. Meta-data revealed a set of 117 genes that were the most commonly affected ranging from 12% to 36% of overlap among breast cancer gene expression studies. Data mining analysis of transcripts and protein-protein interactions of these commonly modulated genes indicate three functional modules signifcantly affected among signatures, one module related with the response to steroid hormone stimulus, and two modules related to the cell cycle. Analysis of a publicly available gene expression data showed that the obtained meta-signature is capable of predicting overall survival (P < 0.0001) and relapse-free survival (P < 0.0001) in patients with early-stage breast carcinomas. In addition, the identifed meta-signature improves breast cancer patient stratifcation independently of traditional prognostic factors in a multivariate Cox proportional-hazards analysis.

Original languageEnglish (US)
Pages (from-to)103-118
Number of pages16
JournalBiomarker Insights
Volume2010
Issue number5
DOIs
StatePublished - 2010

Keywords

  • Biomarkers
  • Breast cancer
  • Gene expression signatures

ASJC Scopus subject areas

  • Molecular Medicine
  • Pharmacology
  • Biochemistry, medical

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