Detection of disease-causing mutations in prostate cancer by NGS sequencing.

Autor: Mangolini A; Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara, Italy., Rocca C; UO Urology, St Anna Hospital, Ferrara, Italy., Bassi C; Department of Translational Medicine, University of Ferrara, Ferrara, Italy., Ippolito C; UO Urology, St Anna Hospital, Ferrara, Italy., Negrini M; Department of Translational Medicine, University of Ferrara, Ferrara, Italy., Dell'Atti L; Division of Urology, Department of Clinical, Special and Dental Science, University Hospital 'Ospedali Riuniti', Marche Polytechnic University, Ancona, Italy., Lanza G; Department of Translational Medicine, University of Ferrara, Ferrara, Italy., Gafà R; Department of Translational Medicine, University of Ferrara, Ferrara, Italy., Bianchi N; Department of Translational Medicine, University of Ferrara, Ferrara, Italy., Pinton P; Department of Medical Sciences, University of Ferrara, Ferrara, Italy., Aguiari G; Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara, Italy.
Jazyk: angličtina
Zdroj: Cell biology international [Cell Biol Int] 2022 Jul; Vol. 46 (7), pp. 1047-1061. Date of Electronic Publication: 2022 Apr 06.
DOI: 10.1002/cbin.11803
Abstrakt: Gene mutations may affect the fate of many tumors including prostate cancer (PCa); therefore, the research of specific mutations associated with tumor outcomes might help the urologist to identify the best therapy for PCa patients such as surgical resection, adjuvant therapy or active surveillance. Genomic DNA (gDNA) was extracted from 48 paraffin-embedded PCa samples and normal paired tissues. Next, gDNA was amplified and analyzed by next-generation sequencing (NGS) using a specific gene panel for PCa. Raw data were refined to exclude false-positive mutations; thus, variants with coverage and frequency lower than 100× and 5%, respectively were removed. Mutation significance was processed by Genomic Evolutionary Rate Profiling, ClinVar, and Varsome tools. Most of 3000 mutations (80%) were single nucleotide variants and the remaining 20% indels. After raw data elaboration, 312 variants were selected. Most mutated genes were KMT2D (26.45%), FOXA1 (16.13%), ATM (15.81%), ZFHX3 (9.35%), TP53 (8.06%), and APC (5.48%). Hot spot mutations in FOXA1, ATM, ZFHX3, SPOP, and MED12 were also found. Truncating mutations of ATM, lesions lying in hot spot regions of SPOP and FOXA1 as well as mutations of TP53 correlated with poor prognosis. Importantly, we have also found some germline mutations associated with hereditary cancer-predisposing syndrome. gDNA sequencing of 48 cancer tissues by NGS allowed to detect new tumor variants as well as confirmed lesions in genes linked to prostate cancer. Overall, somatic and germline mutations linked to good/poor prognosis could represent new prognostic tools to improve the management of PCa patients.
(© 2022 The Authors. Cell Biology International published by John Wiley & Sons Ltd on behalf of International Federation of Cell Biology.)
Databáze: MEDLINE
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