Reclassification of germline BRCA1/2 variants of uncertain significance following breast cancer next generation sequencing (Oral presentation)

Abstract

<p>Background: Germline BRCA1/2 (gBRCA1/2) variants of uncertain significance (VUSs) present challenges for genetic risk assessment and clinical management in breast cancer (BC) patients. Somatic mutational signatures (MS), as the fingerprints of generic mutation patterns, are linked to endogenous and exogenous factors that have influenced cancer development. One specific MS, Signature3 (Sig3), is associated with BRCA1/2 deficiency or homologous recombination deficiency (HRD). This study aims to establish a comprehensive framework for reclassifying gBRCA1/2 VUSs by performing next-generation sequencing (NGS) and analyzing MS via the lens of multi-omics.<br></p><p>Methods: A total of 381 unselected BC patients from Hong Kong underwent comprehensive sequencing, including an 812-gene panel tumor-normal sequencing, RNA sequencing, and DNA methylation sequencing, alongside TCGA-BRCA cohort data to explore our reclassification pipeline preliminarily. From our cohort, we further selected 22 patients with gBRCA1/2 mutations and 20 without for tumor-only whole exome sequencing (WES) on the Illumina platform. We employed a novel computational tool, SigMA, designed to accurately identify HRD-associated MS, particularly in gene panel sequencing data, for the analysis of MS profiling.</p><p><br></p><p>Result: In the TCGA-BRCA cohort, SigMA Sig3 exhibited greater efficiency in detecting biallelic pathogenic BRCA1/2 mutations in WES data compared to gene panel data. In our cohort, we utilized 381 paired panel sequencing data to investigate a tumor-only WES somatic mutation filtering strategy. According to the somatic MS derived from our filtering strategy, SigMA Sig3 successfully identified 100% of pathogenic gBRCA1/2 mutations.<br></p><p>Conclusions: We preliminary found that Sig3 could provide additional evidence to support the reclassification of gBRCA1/2 VUSs and could serve as a predictive biomarker for PARP inhibitor responses. WES might be a better option for more accurate and thorough MS analysis than targeted panel sequencing in clinical setting. This continued research is essential for classifying VUSs to provide enhanced risk assessment and management strategies for affected individuals and families.<br></p>