MicroRNA expression signatures for the prediction of BRCA1/2 mutation‐associated hereditary breast cancer in paraffin‐embedded formalin‐fixed breast tumors |
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| Authors: | Miljana Tanic Kira Yanowski Gonzalo Gómez‐López María Socorro Rodriguez‐Pinilla Iván Marquez‐Rodas Ana Osorio David G. Pisano Beatriz Martinez‐Delgado Javier Benítez |
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| Affiliation: | 1. Human Genetics Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain;2. Bioinformatics Unit, Spanish National Cancer Research Centre (CNIO), Madrid, Spain;3. Pathology Department, Fundación Jimenez Díaz, Madrid, Spain;4. Servicio de Oncología Médica, Instituto de Investigación Sanitaria Gregorio Mara?ón, Madrid, Spain;5. Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Madrid, Spain |
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| Abstract: | Screening for germline mutations in breast cancer‐associated genes BRCA1 and BRCA2 is indicated for patients with breast cancer from high‐risk breast cancer families and influences both treatment options and clinical management. However, only 25% of selected patients test positive for BRCA1/2 mutation, indicating that additional diagnostic biomarkers are necessary. We analyzed 124 formalin‐fixed paraffin‐embedded (FFPE) tumor samples from patients with hereditary (104) and sporadic (20) invasive breast cancer, divided into two series (A and B). Microarray expression profiling of 829 human miRNAs was performed on 76 samples (Series A), and bioinformatics tool Prophet was used to develop and test a microarray classifier. Samples were stratified into a training set (n = 38) for microarray classifier generation and a test set (n = 38) for signature validation. A 35‐miRNA microarray classifier was generated for the prediction of BRCA1/2 mutation status with a reported 95% (95% CI = 0.88–1.0) and 92% (95% CI: 0.84–1.0) accuracy in the training and the test set, respectively. Differential expression of 12 miRNAs between BRCA1/2 mutation carriers versus noncarriers was validated by qPCR in an independent tumor series B (n = 48). Logistic regression model based on the expression of six miRNAs (miR‐142‐3p, miR‐505*, miR‐1248, miR‐181a‐2*, miR‐25* and miR‐340*) discriminated between tumors from BRCA1/2 mutation carriers and noncarriers with 92% (95% CI: 0.84–0.99) accuracy. In conclusion, we identified miRNA expression signatures predictive of BRCA1/2 mutation status in routinely available FFPE breast tumor samples, which may be useful to complement current patient selection criteria for gene testing by identifying individuals with high likelihood of being BRCA1/2 mutation carriers. |
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| Keywords: | hereditary breast cancer miRNA BRCA1 BRCA2 diagnostic biomarker |
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