ArticleFamilial cancer2026
Genetic testing for hereditary breast and ovarian cancer in the Murcian population using a comprehensive NGS panel.
Article in Familial cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Traditionally, hereditary breast and ovarian cancer syndrome (HBOC) has been associated with germline pathogenic or likely pathogenic variants (PV/LPV) in BRCA1 and BRCA2. However, growing evidence indicates that this condition is genetically heterogeneous, and that PV/LPV in additional cancer predisposition genes also contribute significantly to disease susceptibility. In this study, 414 HBOC index cases (ICs) from the Region of Murcia, who fulfilled the 2019 Spanish Society of Medical Oncology (SEOM) criteria, were analyzed using next-generation sequencing (NGS). A 50-gene panel was applied, containing a total of 20 clinically actionable genes recommended by the National Comprehensive Cancer Network (NCCN) for HBOC. The study achieved a diagnostic yield of 15% based solely on the 20 clinically actionable genes included in the panel, with the highest detection rate observed among patients with co-occurring breast and high-grade serous epithelial ovarian cancer. Notably, applying only criteria involving a personal history of breast cancer from the 2019 SEOM guidelines limited the identification of HBOC patients carrying PV/LPV. It was also observed that BRCA genes contributed more to HBOC than non-BRCA genes (60% and 40%, respectively). Finally, re-evaluation of variants of uncertain significance (VUS) led to a substantial reduction in their number, with 25.38% of the initially identified VUS reclassified as benign or likely benign and 6 of the 97 remaining variants (6.2%) prioritized after applying a prioritization algorithm. This study confirms the importance of limiting HBOC genetic testing to clinically actionable genes in routine clinical practice. The re-evaluation and the prioritization of VUS are also essential, since they allow clinical laboratories to manage their resources more efficiently.
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