Pathway-based biomarkers for breast cancer in proteomics

Fan Zhang, Youping Deng, Mu Wang, Li Cui, Renee Drabier

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

Genes do not function alone but through complex biological pathways. Pathway-based biomarkers may be a reliable diagnostic tool for early detection of breast cancer due to the fact that breast cancer is not a single homogeneous disease. We applied Integrated Pathway Analysis Database (IPAD) and Gene Set Enrichment Analysis (GSEA) approaches to the study of pathway-based biomarker discovery problem in breast cancer proteomics. Our strategy for identifying and analyzing pathway-based biomarkers are threefold. Firstly, we performed pathway analysis with IPAD to build the gene set database. Secondly, we ran GSEA to identify 16 pathway-based biomarkers. Lastly, we built a Support Vector Machine model with three-way data split and fivefold cross-validation to validate the biomarkers. The approach-unraveling the intricate pathways, networks, and functional contexts in which genes or proteins function-is essential to the understanding molecular mechanisms of pathway-based biomarkers in breast cancer.

Original languageEnglish (US)
Pages (from-to)101-108
Number of pages8
JournalCancer Informatics
Volume13
Issue numberSuppl 5
DOIs
StatePublished - Jan 1 2014

Keywords

  • Breast cancer
  • Machine learning
  • Pathway analysis
  • Proteomics

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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