Dataset Information

Predicting Ovarian/Breast Cancer Pathogenic Risks of Human BRCA1 Gene Variants of Unknown Significance.

ABSTRACT: High-throughput sequencing is gaining popularity in clinical diagnoses, but more and more novel gene variants with unknown clinical significance are being found, giving difficulties to interpretations of people's genetic data, precise disease diagnoses, and the making of therapeutic strategies and decisions. In order to solve these issues, it is of critical importance to figure out ways to analyze and interpret such variants. In this work, BRCA1 gene variants with unknown clinical significance were identified from clinical sequencing data, and then, we developed machine learning models so as to predict the pathogenicity for variants with unknown clinical significance. Through performance benchmarking, we found that the optimized random forest model scored 0.85 in area under receiver operating characteristic curve, which outperformed other models. Finally, we applied the best random forest model to predict the pathogenicity of 6321 BRCA1 variants from both sequencing data and ClinVar database. As a result, we obtained the predictive pathogenic risks of BRCA1 variants of unknown significance.

SUBMITTER: Lin HH

PROVIDER: S-EPMC8062186 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Predicting Ovarian/Breast Cancer Pathogenic Risks of Human BRCA1 Gene Variants of Unknown Significance.

Lin Hui-Heng HH Xu Hongyan H Hu Hongbo H Ma Zhanzhong Z Zhou Jie J Liang Qingyun Q

BioMed research international 20210414

High-throughput sequencing is gaining popularity in clinical diagnoses, but more and more novel gene variants with unknown clinical significance are being found, giving difficulties to interpretations of people's genetic data, precise disease diagnoses, and the making of therapeutic strategies and decisions. In order to solve these issues, it is of critical importance to figure out ways to analyze and interpret such variants. In this work, BRCA1 gene variants with unknown clinical significance w ...[more]

PMID: 33937409

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Project description:BackgroundThe spectrum of BRCA mutations that predispose to development of breast/ovarian cancer in Indian population remains unexplored. We report incidence and various types of pathogenic, likely pathogenic and variants of unknown significance (VUS) mutations in BRCA1 and BRCA2 genes observed at a tertiary cancer center in North India.Materials and methodsA total of 206 unrelated breast and/or ovarian cancer patients, who met the National Comprehensive Cancer Network (NCCN) guidelines for genetic testing, were screened for germline BRCA1/BRCA 2 mutations on high-throughput sequencing platform; large genomic rearrangements were assessed by multiple ligation probe assay. Mutations were mined in mutational databases, PubMed, and discerned into classes. Furthermore, the clinicopathological correlation of BRCA mutation status with prognostic markers in breast cancer and tumor histology in ovarian cancer was performed.ResultsIn total, 45/206 and 17/206 cases showed positivity for BRCA1 and BRCA2 mutations, respectively, whereas 1/206 was positive for a mutation in both the genes. Altogether, 33 distinct BRCA1 mutations were observed, among which 27 were deleterious (12 frameshifts, 8 nonsense, 1 missense, 3 splice-site variants, 2 big deletions and 1 large duplication) and 6 were VUS. Five novel BRCA1 mutations (c.541G>T, c.1681delT, c.2295delG, c.4915C>T and exon 23 deletion) were identified. Seven mutations (c.2214_2215insT, c.2295delG, c.3607C>T,c.4158_4162delCTCTC, c.4571C>A, splicesite_3 (C>T) and exon 21-23 duplication) occurred more than once, whereas 16 distinct BRCA2 mutations were noted - 9 were lethal (6 frameshifts, 2 nonsense and 1 big deletion) and 7 VUS. One unique pathogenic BRCA2 mutation (c.932_933insT) was recognized. Two mutations (c.9976A>T and c.10089A>G) recurred twice. No significant difference in hormone receptor status was observed among BRCA1 carriers, BRCA2 carriers and noncarriers.ConclusionWe have documented various pathogenic and VUS mutations in BRCA1 and BRCA2 genes observed in the cohort. Six novel mutations were identified. The knowledge shared would assist genetic testing in enabling more focused site-specific screening for mutations in biological relatives.

Dataset Information

Predicting Ovarian/Breast Cancer Pathogenic Risks of Human BRCA1 Gene Variants of Unknown Significance.

Publications

Predicting Ovarian/Breast Cancer Pathogenic Risks of Human BRCA1 Gene Variants of Unknown Significance.

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