Abstract LB-383: Towards automation of germline variant curation in cancer genetics

Abstract

Abstract Cancer care professionals are now increasingly asked to interpret multiplexed gene sequencing of patients at hereditary risk for cancer. Assessments for variant classification now require orthogonal data searches, requiring aggregation of multiple lines of evidence from diverse resources. The burden of evidence required for each variant to meet thresholds for pathogenicity or actionability now poses a growing challenge for those seeking to counsel patients and families following germline genetic testing. A computational tool that automates, provides uniformity and significantly accelerates this interpretive process is required. The automated tool described here, Pathogenicity of Mutation Analyzer (PathoMAN) automates germline genomic variant curation from clinical sequencing based on ACMG guidelines. PathoMAN aggregates multiple tracks of genomic, protein and disease specific information from public sources. When compared against expert curation aggregated from three groups - (i) Prostate Cancer Study; (ii) Breast Cancer Study and (iii) ClinVar. PathoMAN achieves high concordance (83.1% pathogenic, 75.5% benign) and negligible discordance (0.04% pathogenic, 0.9% benign) when contrasted against expert curation. Loss of resolution (8.6% pathogenic, 23.64% benign) and gain of resolution (6.6% pathogenic, 1.6% benign) are observed. We highlight the advantages and weaknesses related to the use of programmable automation of variant classification. PathoMAN provides a substantial advance in rapid classification of genetic variants by generation of robust models using a knowledge-base of diverse genetic data. It is an easily accessible, web-based resource that allows rapid pathogenicity assessment of a large number of variants. We also propose a new nosology for the five ACMG classes to facilitate more accurate reporting to ClinVar. The proposed refinements will better structure ClinVar to allow automation in cancer susceptibility reporting. Such bioinformatics tools are an essential prerequisite to reduce the manual workload of domain level experts. Citation Format: Vignesh Ravichandran, Zarina Shameer, Kenneth Offit, Vijai Joseph. Towards automation of germline variant curation in cancer genetics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-383.