title: Pathway-based Biomarkers for Breast Cancer in Proteomics.
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.
authors.affiliation: Department of Academic and Institutional Resources and Technology, University of North Texas Health Science Center, Fort Worth, TX, USA. ; Department of Forensic and Investigative Genetics, University of North Texas Health Science Center, Fort Worth, TX, USA.
authors.forename: Fan
authors.initials: F
authors.lastname: Zhang
authors.affiliation: Department of Internal Medicine, Rush University Medical Center, Chicago, IL, USA.
authors.forename: Youping
authors.initials: Y
authors.lastname: Deng
authors.affiliation: Department of Biochemistry and Molecular Biology, IU School of Medicine, Indianapolis, IN, USA. ; Indiana Center for Systems Biology and Personalized Medicine, Indianapolis, IN, USA.
authors.forename: Mu
authors.initials: M
authors.lastname: Wang
authors.affiliation: Department of Neurosciences, School of Medicine, University of San Diego, La Jolla, CA, USA.
authors.forename: Li
authors.initials: L
authors.lastname: Cui
authors.affiliation: Department of Academic and Institutional Resources and Technology, University of North Texas Health Science Center, Fort Worth, TX, USA.
authors.forename: Renee
authors.initials: R
authors.lastname: Drabier
keywords: breast cancer; machine learning; pathway analysis; proteomics