Abstract
Abstract Homologous recombination deficiency (HRD) status has been shown to be an effective pharmacogenetic biomarker for determining the efficacy of PARP inhibitor therapy across various tumor types. A functional assessment of the genomic instability associated with HRD is critical as more than half of HRD positive tumors do not have a known causative mutation. Genomic instability is commonly achieved through assessment of three characteristic genomic scars: Loss of heterozygosity (LOH), Telomeric Allelic Imbalance (TAI), & Large-Scale State Transitions (LST) but is challenging due to the need for robust detection of copy number and allelic events genome-wide. As the technology commonly used to analyze tumors varies, we sought to compare the concordance of commonly used platforms to measure genomic instability. Bionano VIA™ software provides a standardized analytical measurement of the genomic scars across technologies, including SNP arrays, pan-cancer gene panels, and optical genome mapping (OGM). The software is uniquely capable to profile solid tumors from pan-cancer sequencing panels, such as the Illumina TruSight Oncology 500 (TSO500) panel, by employing a dynamic binning approach of sequencing data to detect copy number variant (CNV) and LOH events. OGM can detect additional classes of structural rearrangements missed by other technologies to provide new insights into genomic instability. In this study, tumor samples were run on multiple technologies and analyzed in VIA to provide a measurement of the genomic scars. A comparative analysis of each technology’s performance to detect genomic instability through a standardized analytical approach will be described to provide insight into the most effective technologies to assess HRD. Citation Format: Daniel Saul, Megan Roytman, Viren Wasnikar, Rachel Burnside, Alex Hastie, Alka Chaubey. Comprehensive analytical solution to measure HRD genomic scars from SNP arrays, pan-cancer NGS panels, and optical genome mapping (OGM) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 240.
Published Version
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