An integrative bioinformatics approach reveals coding and non-coding gene variants associated with gene expression profiles and outcome in breast cancer molecular subtypes
Győrffy B, Pongor L, Bottai G, Li X, Budczies J, Szabó A, Hatzis C, Pusztai L, Santarpia L. An integrative bioinformatics approach reveals coding and non-coding gene variants associated with gene expression profiles and outcome in breast cancer molecular subtypes. British Journal Of Cancer 2018, 118: 1107-1114. PMID: 29559730, PMCID: PMC5931099, DOI: 10.1038/s41416-018-0030-0.Peer-Reviewed Original ResearchConceptsHER2-negative tumorsBreast cancer patientsCancer patientsER-positive/HER2-negative tumorsBreast cancer molecular subtypesMETABRIC data setMolecular breast cancer subtypesCox regression analysisBreast cancer subtypesCancer molecular subtypesGene expression profilesMann-Whitney U testRegression analysisMultivariate regression analysisPrognostic valueKaplan-MeierBreast cancerClinical dataDisease outcomeTCGA cohortGene expressionMolecular subtypesCancer-associated genesCancer-related genesClinical relevance