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Updated: Jun 16, 2026
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
A fuzzy gene expression-based computational approach improves breast cancer prognostication
Benjamin Haibe-Kains1, Christine Desmedt, Françoise Rothé
1Functional Genomics and Translational Research Unit, Medical Oncology Department, Jules Bordet Institute, Boulevard de Waterloo, Brussels, 1000, Belgium.
Abstract:
Early gene expression studies classified breast tumors into at least three clinically relevant subtypes. Although most current gene signatures are prognostic for estrogen receptor (ER) positive/human epidermal growth factor receptor 2 (HER2) negative breast cancers, few are informative for ER negative/HER2 negative and HER2 positive subtypes. Here we present Gene Expression Prognostic Index Using Subtypes (GENIUS), a fuzzy approach for prognostication that takes into account the molecular heterogeneity of breast cancer. In systematic evaluations, GENIUS significantly outperformed current gene signatures and clinical indices in the global population of patients.