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• W2312791603 abstract "Breast cancer treatment decision-making has been radically changed by the discovery of biomarkers that enable the prescription of stratified therapies according to the cancer genomic subtype. First, estrogen (ER) and progesterone receptors played an important role in the selection of patients for anti-hormonal therapy. Then, human epidermal growth factor receptor 2 (HER2) was validated as predictor of breast cancer response to anti-HER2 therapies. Now, molecular profiling to classify ER-positive breast cancers in luminal A and B types is carried out routinely and triple negative breast cancers tend to be categorized according to their different outcome. Prognostic and predictive biomarkers of the response to hormone/chemotherapy are also needed to identify patients who will benefit from the currently available adjuvant therapies. Several genomic signatures have been described that should outperform these traditional markers, but few are available on the market and their cost-benefit has not been thoroughly assessed yet. New protein biomarkers that can be more easily tested in clinical laboratories are also available. Particularly, uPA and PAI-1 are the only biomarkers validated with the highest level of evidence and recommended by ASCO. Moreover, IHC4 could be used as a surrogate marker at the place of molecular classifiers for ER-positive HER2-negative breast cancers. This review focuses on new protein biomarkers used to refine early-stage breast cancer taxonomy in view of personalized medicine decision-making." @default.
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• W2312791603 date "2015-01-20" @default.
• W2312791603 modified "2023-10-13" @default.
• W2312791603 title "A Refined Taxonomy Based on Protein Biomarkers for Early-Stage Breast Cancer Management" @default.
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• W2312791603 doi "https://doi.org/10.14205/2309-4419.2014.02.02.2" @default.
• W2312791603 hasPublicationYear "2015" @default.
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