Targeted molecular profiling of epithelial ovarian cancer from Italian BRCA wild-type patients with a BRCA and PARP pathways gene panel.

Exp Mol Pathol

Laboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry 'Scuola Medica Salernitana', University of Salerno, 84081 Baronissi, Italy; Genome Research Center for Health - CRGS, Campus of Medicine of the University of Salerno, 84081 Baronissi, SA, Italy. Electronic address:

Published: October 2022

Ovarian cancer (OC) is the fifth most common type of cancer in women and the fourth most common cause of cancer death in women. Identification of pathogenic variants in OC tissues has an important clinical significance for therapeutic and prevention purposes. This study aims to evaluate the mutational profile of a patient cohort, negative for BRCA1/2 germinal variants and Mismatch Repair defects, using next-generation sequencing (NGS) approach on DNA from formalin-fixed paraffin-embedded samples. We used a custom NGS panel, targeting 34 cancer-related genes, mainly of the BRCA and PARP pathways, and analyzed NGS data to identify somatic and germline variants in Italian patients affected by primary epithelial ovarian cancer. We analyzed 75 epithelial ovarian cancer tissues and identified 54 pathogenic variants and 56 variants of unknown significance. TP53 was characterized by the highest mutational rate, occurring in 55% of tested epithelial ovarian cancers (EOCs). Interestingly, a subset of 8 EOCs showed pathogenic variants of homologous recombination pathway, which could be sensitive to PARP-inhibitor therapies. Germline analysis of actionable genes revealed 4 patients carrier of pathogenic germline variants respectively of RAD51C (2 patients), RAD51D, and PALB2. Molecular profiling of EOCs using our custom NGS panel has enabled the detection of both somatic and germline variants, allowing the selection of patients suitable for targeted therapies, and the identification of high-risk OC families that can benefit from genetic counseling and testing.

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Source
http://dx.doi.org/10.1016/j.yexmp.2022.104833DOI Listing

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