Classification and risk stratification of invasive breast carcinomas using a real-time quantitative RT-PCR assay

摘要: Predicting the clinical course of breast cancer is often difficult because it a diverse disease comprised many biological subtypes. Gene expression profiling by microarray analysis has identified signatures that are important for prognosis and treatment. In current article, we use real-time quantitative reverse-transcription (qRT)-PCR assay to risk-stratify cancers based on 'intrinsic' subtypes proliferation. sets were selected from data assess proliferation classify into four different molecular subtypes, designated Luminal, Normal-like, HER2+/ER-, Basal-like. One-hundred twenty-three samples (117 invasive carcinomas, one fibroadenoma five normal tissues) three cell lines prospectively analyzed using (Agilent) qRT-PCR 53 genes. Biological assigned hierarchical clustering. A signature was used as single meta-gene (log2 average 14 genes) predict outcome within context estrogen receptor status subtype. We found could determine intrinsic subtype (93% concordance with microarray-based assignments) predictive outcome. The provided additional prognostic information patients Luminal (P = 0.0012), receptor-positive tumors 3.4 × 10-6). High in conferred 19-fold relative risk relapse (confidence interval 95%) compared low can recapitulate classifications offers an objective measurement grade adds significant