VEEVA APPROVED Accurate Variant Classification and Clinical Impact of Variability

This webinar provides an in-depth exploration of accurate variant classification, focusing specifically on BRCA2 and other Homologous Recombination Repair (HRR) genes, and the clinical impact of classification variability. The session is structured around two main presentations: a scientific deep dive into high-throughput functional assays for BRCA2 variants, and a review of classification challenges and guideline discrepancies observed in recent External Quality Assessment (EQA) runs. The overarching goal is to improve the consistency and accuracy of variant classification, which is critical for clinical management, risk assessment, and therapeutic decisions (such as PARP inhibitor eligibility).

Dr. Fergus Couch details the use of a high-throughput, CRISPR-based technology (MAVE) to functionally evaluate thousands of Variants of Uncertain Significance (VUS) within the key DNA binding domain of BRCA2. This methodology involves inserting every possible single nucleotide change into haploid cells, measuring cell viability over time, and deriving a functional score. The assay demonstrated high sensitivity and specificity (around 95-99%) against known pathogenic and benign standards. By combining this functional data with clinical and genetic evidence within the ACMG AMP classification framework (down-weighting the functional evidence to a PS3/BS3 +4 score for conservatism), the study successfully classified over 90% of the nearly 7,000 variants analyzed, significantly reducing the number of VUS to only 611.

A key advancement discussed was the integration of data from two large, independent CRISPR studies (Mayo Clinic and NCI) using the VarCall statistical model. This integrated approach substantially improved the quality and confidence of classifications, leading to 175 additional variants being classified as pathogenic or likely pathogenic compared to simpler concordance models. Furthermore, the functional classification was validated through large case-control association studies, confirming that variants classified as pathogenic strong (P-strong) were associated with high odds ratios for breast and ovarian cancer, similar to protein-truncating mutations. The presentation also highlighted the identification of hypomorphic (intermediate function) variants, which show partial activity (30-50%) and are associated with intermediate lifetime risks (e.g., 20-25% for breast cancer), suggesting a need to modify risk assessment and management guidelines for these specific variants.

Prof. Thomas Van Overeem Hansen reviewed the learnings from EQA run 14, focusing on the practical challenges of applying classification criteria for ATM, BRCA1, and BRCA2 variants. A major theme was the discrepancy between different gene-specific guidelines, particularly between the ClinGen/Enigma and CanVIG guidelines, regarding the application of criteria like PM2 (absence in control populations) and BS1 (frequency greater than expected). For instance, the guidelines differ on which Nomad version to use (v2.1/3.1 non-cancer cohorts vs. v4.1 focusing on females) and the strength assigned to evidence (e.g., BP1 for missense variants outside functional domains). The review emphasized that such differences can lead to varying final classifications, underscoring the necessity for laboratories to clearly indicate which guidelines and versions were followed in clinical reports, as classification standards are continually evolving.

Detailed Key Takeaways

• High-Throughput Functional Assays are Transforming VUS Classification: CRISPR-based MAVE (Multiplexed Assays of Variant Effect) studies, such as those performed on the BRCA2 DNA binding domain, can classify over 90% of VUS, dramatically reducing the burden on clinical genetics labs and improving patient management.
• Integrated Data Models Enhance Accuracy: Combining data from multiple large-scale functional assays (e.g., two independent CRISPR studies) using sophisticated statistical models like VarCall significantly improves classification quality and confidence, reducing the inherent 5% error rate found in single biological systems.
• Functional Data Must Be Down-Weighted: Even highly accurate functional assays should be conservatively weighted (e.g., PS3/BS3 +4 points in the ACMG framework) to prevent classification based on a single piece of evidence, forcing the requirement for corroborating phenotypic or genetic data to reach likely pathogenic status.
• Hypomorphic Variants Require New Guidelines: A significant number of BRCA2 missense variants exhibit intermediate function and are associated with moderate cancer risks (e.g., 20-25% lifetime breast cancer risk), falling below the high-risk threshold for prophylactic surgery but often above the threshold for enhanced screening (e.g., MRI). These variants necessitate the development of specialized risk assessment and management protocols.
• Classification Guideline Discrepancies Persist: Significant differences exist between major classification bodies (e.g., ClinGen/Enigma vs. CanVIG) regarding the application and weighting of criteria, particularly PM2 (population frequency) and BS1 (benign frequency), including which specific Nomad data sets (v2.1/3.1 non-cancer vs. v4.1 female) should be used.
• Reference Sequence and Nomenclature Clarity is Crucial: EQA results highlight common errors in reporting large genomic alterations (deletions/duplications), often due to inconsistencies in HGVS nomenclature, reference sequences (main transcripts vs. RefSeq), and the use of MLPA probe endpoints. Laboratories should prioritize clear, simple written descriptions and ensure adherence to current, standardized nomenclature.
• PM2 Application Varies by Gene and Guideline: For ATM variants, the application of PM2 (absence in controls) differs between the ClinGen v1.3 publication and the hereditary breast/ovarian/pancreatic cancer VCEP publication, specifically regarding the frequency threshold and the specified Nomad version, highlighting the need to track specific guideline versions.
• BP1 is Gene-Specific: The benign evidence criterion BP1 (missense variant in a gene where truncating variants primarily cause disease) is applicable for BRCA1, BRCA2, and PALB2 missense variants outside functional domains, but explicitly not applicable for ATM variants according to both ClinGen and CanVIG guidelines.
• PM5 Can be Repurposed for PTC Variants: For genes like ATM, PM5 (novel missense change at a residue where a different missense change is pathogenic) can be repurposed to provide supporting evidence for protein-truncating codon (PTC) variants located upstream of a specific codon (e.g., codon 30047 in ATM).
• Functional Studies (BS3) Strength Differs: The strength assigned to benign functional studies (BS3) can vary between guidelines; for example, one specific BRCA2 variant received BS3 strong under Enigma/ClinGen but only BS3 moderate under CanVIG, impacting the final classification score.

Tools/Resources Mentioned

• VEEVA: Mentioned in the title ("VEEVA APPROVED"), indicating the regulatory context of the findings.
• EMQN CIC & GenQA: Organizations responsible for the EQA (External Quality Assessment) runs discussed.
• Genie Platform: Genomic Online Individual Education platform used by GenQA for EQA delivery.
• ClinVar: Database used as a standard for VUS classification comparison.
• Nomad (v2.1, v3.1, v4.1): Genomic data sets used for population frequency analysis (PM2, BS1 criteria).
• ClinGen Criteria Specification Registry: Resource for finding the most recent classification guidelines.
• CanVIG: Classification working group whose guidelines are compared against Enigma/ClinGen.
• VarCall Model: Statistical model developed by Ed Iverson (Duke University) used for batch correction and integrating multiple functional assay data sets.

Key Concepts

• Variants of Uncertain Significance (VUS): Genetic variants whose effect on protein function and pathogenicity is currently unknown, posing a major challenge for clinical management.
• MAVE (Multiplexed Assays of Variant Effect): High-throughput functional assays (often CRISPR-based) that allow simultaneous testing of thousands of single nucleotide variants to determine their functional impact (e.g., viability, DNA repair capacity).
• Hypomorphic/Intermediate Variants: Variants that retain partial protein function (e.g., 30-50% activity) and are associated with moderate, rather than high, lifetime cancer risk.
• ACMG AMP Guidelines: The standard framework (developed by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology) for interpreting sequence variants, often adapted by gene-specific expert panels (VCEPs) like Enigma and CanVIG.
• EQA (External Quality Assessment): Proficiency testing schemes (like those run by EMQN/GenQA) used to assess the competency and consistency of laboratories in applying variant classification guidelines.
• Homologous Recombination Repair (HRR) Genes: A group of genes, including BRCA1, BRCA2, ATM, PALB2, and CHECK2, critical for DNA double-strand break repair, whose inactivation increases cancer risk.