Whole Genome Landscape Analysis of Homologous Recombination Deficiency in a Pan-Cancer Cohort

Abstract

AbstractPurposeHomologous recombination deficiency (HRD) impacts cancer treatment strategies, particularly the effectiveness of PARP inhibitors. However, the variability different HRD assays has hampered the selection of oncology patients who may benefit from these therapies. Our study aims to assess the whole genome landscape to better define HRD in a pan-cancer cohort and to contribute to harmonization of HRD detection.MethodsWe employed a whole-genome sequencing WGS HRD classifier that included genome-wide features associated with HRD to analyze 580 tumor/normal paired pan-cancer samples. The HRD results were correlated retrospectively with treatment responses and were compared with commercial HRD tests in a subset of cases.ResultsHRD phenotype was identified in 62 samples across various cancers including breast (19%), pancreaticobiliary (17%), gynecological (15%), prostate (8%), upper gastrointestinal (GI) (2%), and other cancers (1%). HRD cases were not confined toBRCA1/2mutations; 24% of HRD cases wereBRCA1/2wild-type. A diverse range of HRR pathway gene alterations involved in HRD were elucidated, including biallelic mutations inFANCF, XRCC2, andFANCC, and deleterious structural variants. Comparison with results from commercial HRD assays suggests a better performance of WGS to detect HRD, based on treatment response.ConclusionHRD is a biomarker used to determine which cancer patients would benefit from PARPi and platinum-based chemotherapy. However, a lack of harmonization of tests to determine HRD status makes it challenging to interpret their results. Our study highlights the use of comprehensive WGS analysis to predict HRD in a pan-cancer cohort, elucidates new genomic mechanisms associated with HRD, and enables an accurate identification of this phenotype, paving the way for improved outcomes in oncology care.