Oncology

Tumour characteristics provide evidence for germline mismatch repair variant pathogenicity

Abstract

Background

Pathogenic variants in mismatch repair (MMR) genes (MLH1, MSH2MSH6 and PMS2) increase risk for Lynch syndrome and related cancers. We quantified tumour characteristics to assess variant pathogenicity for germline MMR genes.

Methods

Among 4740 patients with cancer with microsatellite instability (MSI) and immunohistochemical (IHC) results, we tested MMR pathogenic variant association with MSI/IHC status, and estimated likelihood ratios which we used to compute a tumour characteristic likelihood ratio (TCLR) for each variant. Predictive performance of TCLR in combination with in silico predictors, and a multifactorial variant prediction (MVP) model that included allele frequency, co-occurrence, co-segregation, and clinical and family history information was assessed.

Results

Compared with non-carriers, carriers of germline pathogenic/likely pathogenic (P/LP) variants were more likely to have abnormal MSI/IHC status (p<0.0001). Among 150 classified missense variants, 73.3% were accurately predicted with TCLR alone. Models leveraging in silico scores as prior probabilities accurately classified >76.7% variants. Adding TCLR as quantitative evidence in an MVP model (MVP +TCLR Pred) increased the proportion of accurately classified variants from 88.0% (MVP alone) to 98.0% and generated optimal performance statistics among all models tested. Importantly, MVP +TCLR Pred resulted in the high yield of predicted classifications for missense variants of unknown significance (VUS); among 193 VUS, 62.7% were predicted as P/PL or benign/likely benign (B/LB) when assessed according to American College of Medical Genetics and Genomics/Association for Molecular Pathology guidelines.

Conclusion

Our study demonstrates that when used separately or in conjunction with other evidence, tumour characteristics provide evidence for germline MMR missense variant assessment, which may have important implications for genetic testing and clinical management.

  • Authors: Shuwei Li; Dajun Qian; Bryony A Thompson; Stephanie Gutierrez; Sitao Wu; Tina Pesaran; Holly LaDuca; Hsiao-Mei Lu; Elizabeth C. Chao; Mary Helen Black
  • Journal: American journal of medical genetics
  • Date: 2019 - Aug

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