Cells · 2020 · 30 citations · 39 references
MedicineCancer BiologyOncologyBreast OncologyEndocrine OncologyMolecular OncologyBreast Cancer OncologyCancer TranscriptomicsEndocrine Tumor PrognosisMammary TumorsAndrogen Receptor ExpressionBreast Cancer HistopathologyBreast Cancer Molecular SubtypesCellular ProliferationEstrogen Receptor StatusHormone Receptor - Positive Breast CancerMalignant Breast TumorsProliferation Pathways
The co-expression of androgen (AR) and estrogen (ER) receptors, in terms of higher AR/ER ratio, has been recently associated with poor outcome in ER-positive (ER+) breast cancer (BC) patients. The aim of this study was to analyze if the biological aggressiveness, underlined in ER+ BC tumors with higher AR/ER ratio, could be due to higher expression of genes related to cell proliferation. On a cohort of 47 ER+ BC patients, the AR/ER ratio was assessed by immunohistochemistry and by mRNA analysis. The expression level of five gene proliferation markers was defined through TaqMan®-qPCR assays. Results were validated using 979 BC cases obtained from gene expression public databases. ER+ BC tumors with ratios of AR/ER ≥ 2 have higher expression levels of cellular proliferation genes than tumors with ratios of AR/ER < 2, in both the 47 ER+ BC patients (P < 0.001) and in the validation cohort (P = 0.005). Moreover, BC cases with ratios of AR/ER ≥ 2 of the validation cohort were mainly assigned to luminal B and HER2-enriched molecular subtypes, typically characterized by higher proliferation and poorer prognosis. These data suggest that joint routine evaluation of AR and ER expression may identify a unique subset of tumors, which show higher levels of cellular proliferation and therefore a more aggressive behavior.
39
Gene expression profiling predicts clinical outcome of breast cancer
Laura van ‘t Veer, Hongyue Dai, Marc J. van de Vijver et al. · Nature · 2002 · 9.6K citations · Full text
Supervised Risk Predictor of Breast Cancer Based on Intrinsic Subtypes
Joel S. Parker, Michael E. Mullins, Maggie C.U. Cheang et al. · Journal of Clinical Oncology · 2009 · 4.9K citations · Full text
Medicine, Bioinformatics, Oncology +16
TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data
Antonio Colaprico, Tiago C. Silva, Catharina Olsen et al. · Nucleic Acids Research · 2015 · 4.5K citations · Full text
M. Elizabeth H. Hammond, Daniel F. Hayes, Mitch Dowsett et al. · Journal of Clinical Oncology · 2010 · 4.3K citations · Full text
Medicine, Cancer Biology, Oncology +14