ArticleScientific reports2021
In silico analysis of BRCA1 and BRCA2 missense variants and the relevance in molecular genetic testing.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed, 22 citations in OpenAlex.
- In Silico Functional and Structural Analysis ofGenes · 2026Article
- Genetic variants inThe Libyan journal of medicine · 2025Article
- Report of a missense TJP2 variant associated to PFIC4 with a pronounced phenotypic variability: Focus on the structural effects on the protein level.Journal of human genetics · 2025Article
- Computational prediction of deleterious nonsynonymous SNPs in the CTNS gene: implications for cystinosis.BMC genomic data · 2025Article
- AI-derived comparative assessment of the performance of pathogenicity prediction tools on missense variants of breast cancer genes.Human genomics · 2024Article
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- Functional evaluation of BRCA1/2 variants of unknown significance with homologous recombination assay and integrative in silico prediction model.Journal of human genetics · 2023Article
- A review of genetic variant databases and machine learning tools for predicting the pathogenicity of breast cancer.Briefings in bioinformatics · 2023Review
- Bioinformatic analysis of genetic changes CLOCK, BMAL1, CRY1, CRY2, PER1, PER2, PER3, and NPAS2 proteins in HCC patients.Hepatology forum · 2023Article
- Understanding and predicting the functional consequences of missense mutations in BRCA1 and BRCA2.Scientific reports · 2022Article
- Validation and Data-Integration of Yeast-Based Assays for Functional Classification of BRCA1 Missense Variants.International journal of molecular sciences · 2022Article
- Analysis of single-nucleotide polymorphisms in genes associated with triple-negative breast cancer.Frontiers in genetics · 2022Article
- Computational approaches for predicting variant impact: An overview from resources, principles to applications.Frontiers in genetics · 2022Review
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1 author at 1 institution in 1 country.
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Abstract
Over the years since the genetic testing of BRCA1 and BRCA2 has been conducted for research and later introduced into clinical practice, a high number of missense variants have been reported in the literature and deposited in public databases. Polymorphism Phenotyping v2 (PolyPhen-2) and Sorting Intolerant from Tolerant (SIFT) are two widely applied bioinformatics tools used to assess the functional impacts of missense variants. A total of 2605 BRCA1 and 4763 BRCA2 variants from the ClinVar database were analysed with PolyPhen2 and SIFT. When SIFT was evaluated alongside PolyPhen-2 HumDiv and HumVar, it had shown top performance in terms of negative predictive value (NPV) (100%) and sensitivity (100%) for ClinVar classified benign and pathogenic BRCA1 variants. Both SIFT and PolyPhen-2 HumDiv achieved 100% NPV and 100% sensitivity in prediction of pathogenicity of the BRCA2 variants. Agreement was achieved in prediction outcomes from the three tested approaches in 55.04% and 68.97% of the variants of unknown significance (VUS) for BRCA1 and BRCA2, respectively. The performances of PolyPhen-2 and SIFT in predicting functional impacts varied across the two genes. Due to lack of high concordance in prediction outcomes among the two tested algorithms, their usefulness in classifying the pathogenicity of VUS identified through molecular testing of BRCA1 and BRCA2 is hence limited in the clinical setting.
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