bioRxivCancer BiologyPreprint
Genomic aberration based molecular signatures efficiently characterize homologous recombination deficiency in prostate cancer
Z. Sztupinszki, M. Diossy, M. Krzystanek, J. Borcsok, M. Pomerantz, V. Tisza, S. Spisak, O. Rusz, I. Csabai, M. Freedman, Z. Szallasi
Abstract
BackgroundProstate cancers with mutations in genes involved in homologous recombination (HR), most commonly BRCA2, respond favorably to PARP inhibition and platinum-based chemotherapy. It is not clear, however, whether other prostate tumors that do not harbor deleterious mutations in these particular genes can similarly be deficient in HR, rendering them sensitive to HR-directed therapies.\n\nTo identify a more comprehensive set of prostate cancer cases with homologous recombination deficiency (HRD) including those cases that do not harbor mutations in known HR genes.\n\nHRD levels can be estimated using various mutational signatures derived from next-generation sequencing data. We used this approach to determine whether prostate cancer cases display clear signs of HRD in somatic tumor biopsies. Whole genome (n=311) and whole exome sequencing data (n=498) of both primary and metastatic prostate adenocarcinomas (PRAD) were analyzed.\n\nResultsKnown BRCA-deficient samples showed robust signs of HR-deficiency associated mutational signatures. HRD-patterns were also detected in a subset of patients who did not harbor germline or somatic mutations in BRCA1/2 or other HR related genes. Patients with HRD signatures had a significantly worse prognosis than patients without signs of HRD.\n\nConclusionsThese findings may expand the number of cases likely to respond to PARP-inhibitor treatment. Based on the HRD associated mutational signatures, 5-8 % of prostate cancer cases may be good candidates for PARP-inhibitor treatment (including those with BRCA1/2 mutations).
- organism: human
- assay: whole-genome sequencing
- assay: whole-exome sequencing
- research focus: differential expression
- research focus: variant calling
- approach: statistical model
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