On January 8, 2025 Ambry Genetics, a leader in clinical genomic testing, reported its contribution to a study published in Nature that significantly advances our understanding of BRCA2 gene variants (Press release, Ambry Genetics, JAN 8, 2025, View Source [SID1234649524]). As the uptake of genetic testing continues to grow, the need for scalable interpretation of the vast number of variants detected has become critical. This study was designed to leverage CRISPR/cas-9 gene editing to aid in the functional characterization of nearly 7,000 BRCA2 variants, helping to resolve variants of uncertain significance (VUS) and guide better clinical management.
Schedule your 30 min Free 1stOncology Demo!
Discover why more than 1,500 members use 1stOncology™ to excel in:
Early/Late Stage Pipeline Development - Target Scouting - Clinical Biomarkers - Indication Selection & Expansion - BD&L Contacts - Conference Reports - Combinatorial Drug Settings - Companion Diagnostics - Drug Repositioning - First-in-class Analysis - Competitive Analysis - Deals & Licensing
Schedule Your 30 min Free Demo!
BRCA2 is a well-established and clinically actionable gene associated with cancer predisposition.1 Testing BRCA2 has long been a staple of hereditary cancer testing, as pathogenic variants in the gene are associated with cancers of the breast, ovary, prostate, and pancreas.2-5 Despite the well-understood importance of BRCA2, at the time of this research, more than 5,000 BRCA2 variants are categorized as VUS in the National Institute of Health’s (NIH) ClinVar database (a catalogue of genomic variants and their classifications). Many of these are classified as VUS because there has been insufficient evidence to their classification.6
The study, led by Fergus J. Couch, PhD, of Mayo Clinic, brought together an interdisciplinary team of researchers from Mayo Clinic, H. Lee Moffitt Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Hospital Clinico San Carlos, Memorial Sloan Kettering Cancer Center, and Duke University, as well as Ambry Genetics, to understand and evaluate BRCA2 variants for their functional contributions to cancer pathogenesis.
The results of this study were integrated into a ClinGen/ACMG/AMP model for clinical interpretation, resulting in a 91% rate of classification showing the promise for improving the future of hereditary cancer testing results across all test providers.
"These findings illustrate the power of integrating functional genetic data with clinical analysis to improve understanding of hereditary cancer risk and optimize clinical management approaches," said Marcy Richardson, PhD, Associate Director of Clinical Research at Ambry Genetics. "Functional testing of cancer-associated genes enables the clinical community to offer patients better data-informed recommendations on how best to mitigate cancer risk."
"These findings demonstrate the value of collaborative research in advancing our understanding of BRCA2 variants, improving classification methods that support more accurate risk assessments and informed clinical care," said Fergus Couch, Ph.D., Professor at Mayo Clinic and lead author of the study. "By integrating functional studies with clinical data, we can provide clinicians with valuable tools to guide patients in managing their hereditary cancer risks."
"Genetic testing and variant analysis are paving the way towards truly personalized clinical care for patients before they have cancer, moving us well beyond the time when clinical decision-making based on family history left many clinicians and patients feeling powerless to intervene prior to cancer onset," said Elizabeth Chao, MD, FACMG, Chief Medical Officer at Ambry Genetics. "Improving the quality of data available in our genetic databases allows us to better classify variants across diverse populations, offering a more inclusive approach to genetic testing, giving clinicians new tools for recommending measures to prevent cancer."
This paper is co-published alongside another related study with the NIH, which examines the same issues using a different model. Together, these studies represent a major step forward in variant classification, providing essential data that helps clinicians better assess cancer risks tied to genetic mutations.