ArticleCancer management and research2025
The Frequency and Reclassification of Variants Uncertain Significance in Hereditary Breast and Ovarian Cancer Among Levantine Patients.
Article in Cancer management and research, 2025. 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
Introduction: The evolution of genetic sequencing technologies in Hereditary Breast and Ovarian Cancer (HBOC) from BRCA1/2 analysis to multigene panel sequencing was paralleled with a significant increase in the number of detected variants of uncertain significance (VUS). This trend was found to particularly affect minority populations, such as the underrepresented Middle Eastern population. This study aims at assessing the prevalence and reclassification potential of VUS in a cohort of Levantine patients at risk of HBOC. Methods: A retrospective chart review of patients at risk of HBOC tested at the American University of Beirut Medical Center between years 2010 and 2019 was conducted. Genetic testing results, as well as epidemiological, clinical and pathology data were extracted for 347 patients. Review and reclassification of VUS were performed according to the latest ACMG/AMP criteria and the ClinGen ENIGMA methodology. Data were analyzed in SPSS v29 using Chi-square and one way ANOVA tests, with p ≤ 0.05 as significant. Significant results were reviewed for confounders using multivariate regression. Results: 160 genomic alterations classified as VUS were detected. Of those, 32.5% were reclassified, including 4 variants upgraded to pathogenic/likely pathogenic. Non-informative results were present in 40% of participants, with a median of 4 total VUS per patient (mean ACMG pathogenicity score: 3.77). VUS carriers were more likely to have a personal history of breast cancer (72%), specifically triple negative breast cancer (19%). Conclusion: These findings reveal a high burden of non-informative variants in our population, yet lack of external and functional validation limit the generalizability of our study. Improved genetic diversity in reference datasets and regionally adapted classification strategies are required.
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