BRCA2 Polymorphisms and Breast Cancer Susceptibility: a Multi-Tools Bioinformatics Approach

Area of Science:

• Genomics
• Bioinformatics
• Cancer Genetics

Background:

• The BRCA2 gene plays a crucial role in DNA repair and maintaining genomic stability.
• Mutations in BRCA2 are strongly associated with an increased risk of hereditary breast and ovarian cancers.
• Identifying specific deleterious single nucleotide polymorphisms (SNPs) in BRCA2 is vital for understanding cancer susceptibility.

Purpose of the Study:

• To computationally identify deleterious single nucleotide polymorphisms (SNPs) within the BRCA2 gene.
• To predict the functional impact and pathogenicity of identified BRCA2 SNPs.
• To provide a foundation for understanding breast cancer susceptibility and developing targeted therapies.

Main Methods:

• Utilized the GenomAD database to identify SNPs in the BRCA2 gene.
• Employed multiple in silico prediction tools (SIFT, PolyPhen, PredictSNP, SNAP2, PhD-SNP, ClinVar) to assess SNP consequences.
• Evaluated pathogenicity using MutPred and Fathmm, protein stability with I-Mutant and MuPro, and conservation analysis.

Main Results:

• Identified 7,921 SNPs, including 1940 missense SNPs.
• A consensus identified 69 damaging SNPs across all prediction platforms.
• Found 48 and 38 SNPs associated with cancer risk by Mutpred and Fathmm, respectively; 22 SNPs predicted to decrease protein stability.
• Pinpointed 18 deleterious mutations in critical DNA binding domains and one in the BRC repeat region.

Conclusions:

• This in silico study provides a prioritized list of deleterious BRCA2 SNPs.
• The findings lay the groundwork for future experimental validation of these SNPs.
• The identified mutations can inform the development of targeted breast cancer treatment strategies.