BRCA Share

BRCA Share enables annotation and classification of BRCA1 and BRCA2 genetic variants to assess their contribution to hereditary breast and ovarian cancer predisposition.

Key Features:

• UMD-BRCA1/BRCA2 database integration: Leverages the UMD-BRCA1/BRCA2 databases as a comprehensive repository of causal, neutral, and unclassified variants (UVs) observed in France.
• Co‑occurrence data analysis: Includes co-occurrence data for all variants to analyze correlations and potential interactions between variants.
• Variant annotation and classification: Provides annotation and classification of UVs in BRCA1 and BRCA2 into causal or neutral categories where supported by data.
• Structural three‑dimensional analysis: Applies a structural approach that analyzes the three-dimensional structure of BRCA proteins to assess potential impacts of variants on protein function and stability.
• Cross-database comparison: Cross-references variants with external resources such as the BIC database to support classification and validation of UVs.

Scientific Applications:

• BRCA variant interpretation: Annotates and classifies BRCA1 and BRCA2 variants to support interpretation of pathogenicity for hereditary breast and ovarian cancer studies.
• Structural impact assessment: Assesses how specific genetic changes may alter BRCA protein function or stability through three-dimensional structural analysis.
• Population variant cataloguing: Utilizes a nationwide repository of BRCA variants to characterize the spectrum of causal, neutral, and unclassified variants in France.
• Co‑occurrence and interaction analysis: Identifies variant co-occurrence patterns that may inform variant classification and hypotheses about variant interactions.
• Cross-database validation: Enables comparison of novel or unclassified variants against databases such as BIC for corroboration of findings.

Methodology:

Computational methods explicitly include integration of UMD-BRCA1/BRCA2 database records, analysis of variant co-occurrence, three-dimensional structural analysis of BRCA proteins to evaluate variant effects on function and stability, and cross-referencing variants with the BIC database.