# Robust Predictor of Breast Cancer Risk > **NIH NIH R42** · MORGAN AND MENDEL GENOMICS, INC. · 2020 · $991,797 ## Abstract Approximately 1.5 million women in the United States are at high-risk for developing breast cancer, based on inheritance of a germline mutation in a gene in the double strand-break (DSB) repair and cyclin-checkpoint pathways. Many are unaware of their genetic predispositions, because their family history is uninformative or unknown. Genetic testing is important for identifying mutations in these genes, but in ~80% of cases no mutation is identified, leading to ambiguous, unsatisfactory results. Identifying women at high risk prior to the onset of disease is an important challenge for personalized medicine, because disease can be prevented or treated at the earliest stage when cure is more likely. As more women are seeking genetic testing to identify their risk of breast cancer, accurate alternatives to sequencing are needed to predict the molecular phenotypic effects of mutations in genes in breast cancer-predisposing pathways. Risk classification scores based on flow variant assays (FVAs) are a new technology that can accurately identify women with heterozygous germline mutations in these pathways. FVAs are rapid, inexpensive and highly reproducible and can be performed on circulating and cultured human blood cells, thus lending themselves to becoming a Next Generation, non- sequencing, standalone test. The goal of this STTR project is to develop a simple, rapid and inexpensive clinical test that will accurately identify those at high risk for breast cancers. Phase I hypothesis: The standalone FVA test using whole blood samples will identify those at high-risk with 95% accuracy. Specific aim 1. Achieve risk classification score results for 99% of subjects with at least 95% accuracy on 180 subjects from well-characterized risk groups. Specific aim 2. Achieve risk classification score results for all subjects from Aim 1 with comparable accuracy using an automated analysis protocol and newly created commercial kit. Having demonstrated the analytical validity in Phase I, MMG will demonstrate clinical utility in Phase II by calculating and validating 10-year hazard ratios for breast cancer by age decade for 1,800 women followed by up to 20 years by the NCI’s Breast Cancer Family Registry. In addition, MMG will demonstrate the analytical validity of this test analytical validity and reproducibility of FVA test kits in-house and at collaborating laboratories, demonstrate the roles of mutations in high and moderate-penetrance DSB repair genes in modifying FVA traits, and demonstrate the stability of FVA traits over time and whether these are affected by exposure to chemotherapy. This product will be sold to clinical laboratories in collaboration with a designated good manufacturing practices facility commercial partner as an FDA approved test. Several factors will drive this commercialization into the $1B market cancer risk assessment market: 1. low entry and performance costs, 2. greater accuracy than sequencing, 3. application to understanding risks f... ## Key facts - **NIH application ID:** 10079935 - **Project number:** 2R42CA217383-02A1 - **Recipient organization:** MORGAN AND MENDEL GENOMICS, INC. - **Principal Investigator:** Harry Ostrer - **Activity code:** R42 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $991,797 - **Award type:** 2 - **Project period:** 2017-09-20 → 2022-06-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10079935 ## Citation > US National Institutes of Health, RePORTER application 10079935, Robust Predictor of Breast Cancer Risk (2R42CA217383-02A1). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10079935. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*