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Objectives: To develop a validated model for evaluating the real-world effectiveness of long-term clinical management strategies for women with germline BRCA1 or BRCA2 pathogenic variants., Methods: A microsimulation model was developed that included a BRCA-specific natural history for breast and ovarian cancer, a clinical framework for carrier follow-up, and cancer risk management strategies (breast screening, risk-reducing mastectomy, and bilateral salpingo-oophorectomy). Adherence rates and outcomes for breast screening and risk-reducing surgery were obtained from BRCA carriers seen through a familial cancer service in Melbourne, Australia. The model was assessed for internal and external validity. The model was used to compare women perfectly adhering to screening recommendations versus actual adherence of the clinical cohort., Results: The model accurately predicted cancer incidence, pathology, and mortality. Using actual adherence for breast screening resulted in additional breast cancer deaths (per 1000 women: BRCA1, 2.7; BRCA2, 1.6) compared with perfect screening adherence. This decreased average life expectancy by 0.30 life-years for BRCA1 and 0.07 life-years for BRCA2. When carriers had access to risk-reducing mastectomy, the benefit from improved screening adherence was not significant., Conclusions: The developed model is a good descriptor of BRCA carriers' lifetime trajectory and its modification by use of risk management strategies alone or in combination. Evaluations of breast screening in BRCA carriers may overestimate the benefits of screening programs unless adherence is considered. By incorporating real-world clinical practice and patient behavior, this model can assist in developing clinical services and improving clinical outcomes for carriers., (Copyright © 2019 ISPOR–The Professional Society for Health Economics and Outcomes Research. Published by Elsevier Inc. All rights reserved.)

BRCA2 (breast cancer 2, early onset) is a tumor suppressor gene that confers increased susceptibility for prostate cancer (PCa). Previous in vitro experiments demonstrated that Skp2, an E3 ubiquitin ligase aberrantly overexpressed in PCa, is involved in the proteolytic degradation of BRCA2 in PCa cells, suggesting that the BRCA2-Skp2 interaction may play a role in prostate tumorigenesis. Herein, we investigated BRCA2 and Skp2 expression during PCa development using a prostate TMA. Although luminal and basal benign prostate epithelium exhibited moderate to strong nuclear BRCA2 immunostaining, the intensity and number of positive nuclei decreased significantly in high-grade prostatic intraepithelial neoplasia and PCa. Decreased frequency and intensity of nuclear BRCA2 labeling were inversely correlated with Skp2 expression in high-grade prostatic intraepithelial neoplasia and PCa. To functionally assess the effects of BRCA2 and Skp2 expression on prostate malignant transformation, we overexpressed Skp2 in normal immortalized prostate cells. Skp2 overexpression reduced BRCA2 protein and promoted cell growth and migration. A similar phenotype was observed after reduction of BRCA2 protein levels using specific BRCA2 small-interfering RNA. Forced BRCA2 expression in Skp2-overexpressing stable transfectants inhibited the migratory and growth properties by >60%. These results show that loss of BRCA2 expression during prostate tumor development is strongly correlated with both migratory behavior and cancer growth and include Skp2 as a BRCA2 proteolytic partner in vivo., (Copyright © 2011 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

Background: BRCA1 and BRCA2 are breast cancer susceptibility genes. Recent studies suggest that BRCA1 interacts with a great variety of proteins, including BRCA2, cell-cycle regulators, transcriptional activators and repressors. We investigated the expression of both BRCA1 and BRCA2 during the progression of the cell cycle of human tumor cell lines from different origins (MCF7, MDA-MB231, PA1 and CCL221) in two growth status (60% and 100% of confluency)., Methods: First, the growth status was characterized by determination of the cell cycle by flow cytometry analysis. At the same time, immunohistochemistry was performed to follow BRCA1 and BRCA2 protein expression and then, quantification of BRCA1 and BRCA2 transcripts was realized using real-time quantitative RT-PCR., Results: We reported in studied tumor cell lines with 60% of confluency by comparison with 100% of confluency, an increase in the BRCA1 and BRCA2 expression at the level of proteins and transcripts., Conclusion: Therefore, the expression of both BRCA1 and BRCA2 genes at the protein and mRNA levels appear to be up-regulated after cell proliferation in human tumor cell lines from different origins.

Large proportions of hereditary breast cancers are due to mutations in the two breast cancer susceptibility genes BRCA1 and BRCA2. Considerable effort has gone into studying the function(s) of these tumor suppressor genes, both in attempts to better understand why individuals with these inherited mutations acquire breast (and ovarian) cancer and to potentially develop better treatment strategies. The advent of tools such as cDNA microarrays has enabled researchers to study global gene expression patterns in, for example, primary tumors, thus providing more comprehensive overviews of tumor development and progression. Our recent study (Hedenfalk et al., 2001) strongly supports the principle that genomic approaches to classification of hereditary breast cancers are possible, and that further studies will likely identify the most significant genes that discriminate between subgroups and may influence prognosis and treatment. A large number of hereditary breast cancer cases cannot be accounted for by mutations in these two genes and are believed to be due to as yet unidentified breast cancer predisposition genes (BRCAx). Subclassification of these non-BRCA1/2 breast cancers using cDNA microarray-based gene expression profiling, followed by linkage analysis and/or investigation of genomic alterations, may help in the recognition of novel breast cancer predisposition loci. To summarize, gene expression-based analysis of hereditary breast cancer can potentially be used for classification purposes, as well as to expand upon our knowledge of differences between different forms of hereditary breast cancer. Initial studies indicate that a patient's genotype does in fact leave an identifiable trace on her/his cancer's gene expression profile.