Enhanced detection and characterization of germline structural variants in cancer predisposition genes via genome sequencing

This is the authors' abstract. We don't add key points for this paper.

Purpose: Germline pathogenic variants in cancer predisposition genes are found in approximately 10% of all cancer cases. Although multigene panel testing is the current first-tier approach for detecting variants in these genes, it has limitations in identifying and characterizing copy-number variants and other structural variants (SVs). Genome sequencing (GS) provides a more uniform coverage throughout the genome, thereby offering a more comprehensive method for copy-number variant and SV detection; however, its diagnostic utility in genetic testing for cancer predisposition remains underexplored. Methods: In this study, we performed GS on 33 patients with previously identified germline SVs in cancer predisposition genes, including 25 deletions, 7 duplications, and 1 mobile element insertion. Results: Using 2 SV callers in the DRAGEN pipeline, GS achieved 100% sensitivity in detecting these SVs. Moreover, GS revealed additional insights not available through previous clinical testing in 9 (27%) cases, including identifying a complex SV, clarifying structural configuration of intragenic duplications, and refining breakpoints at base-pair resolution. Conclusion: Taken together, our findings support the utility of GS as the sequencing backbone for germline genetic testing of cancer predisposition genes with improved detection, characterization, and clinical interpretation of SVs.