title: Breast cancer classification: linking molecular mechanisms to disease prognosis.
abstract: Breast cancer was traditionally perceived as a single disease; however, recent advances in gene expression and genomic profiling have revealed that breast cancer is in fact a collection of diseases exhibiting distinct anatomical features, responses to treatment and survival outcomes. Consequently, a number of schemes have been proposed for subtyping of breast cancer to bring out the biological and clinically relevant characteristics of the subtypes. Although some of these schemes capture underlying molecular differences, others predict variations in response to treatment and survival patterns. However, despite this diversity in the approaches, it is clear that molecular mechanisms drive clinical outcomes, and therefore an effective scheme should integrate molecular as well as clinical parameters to enable deeper understanding of cancer mechanisms and allow better decision making in the clinic. Here, using a large cohort of ∼550 breast tumours from The Cancer Genome Atlas, we systematically evaluate a number of expression-based schemes including at least eight molecular pathways implicated in breast cancer and three prognostic signatures, across a variety of classification scenarios covering molecular characteristics, biomarker status, tumour stages and survival patterns. We observe that a careful combination of these schemes yields better classification results compared with using them individually, thus confirming that molecular mechanisms and clinical outcomes are related and that an effective scheme should therefore integrate both these parameters to enable a deeper understanding of the cancer.
authors.forename: Atefeh
authors.initials: A
authors.lastname: Taherian-Fard
authors.forename: Sriganesh
authors.initials: S
authors.lastname: Srihari
authors.forename: Mark A
authors.initials: MA
authors.lastname: Ragan
mesh_terms: D014408:Biomarkers, Tumor / Q000378:metabolism*; D001943:Breast Neoplasms / Q000145:classification / Q000175:diagnosis* / Q000378:metabolism*; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D025202:Molecular Diagnostic Techniques / Q000379:methods*; D009363:Neoplasm Proteins / Q000378:metabolism*; D011379:Prognosis; D025941:Protein Interaction Mapping / Q000379:methods; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods; D012680:Sensitivity and Specificity
chemical_list: D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins
keywords: biomarkers; breast cancer classification; clinical subtypes; gene expression; molecular signature