Abstract 5456: Clinical validation of NAVIFY® Mutation Profiler for solid tumor NGS variant interpretation
Authors: Sidney Alexander Scudder, Anoop Grewal, Lisha Capucion, Guili Zhang, Leonid Formin, Shuba Krishna, Xi Decker, Joanie Chung
Journal: Cancer Research (2020)

Abstract Introduction: Next-Generation Sequencing (NGS) is a standard of care for identifying actionable mutations in solid tumors. Data analysis and adjudication of variants is a significant barrier to NGS adoption in community settings. NAVIFY® Mutation Profiler (NMP) is a cloud-based software that provides curation, annotation, interpretation and reporting of somatic genomic variants identified by NGS. NMP is agnostic to the sample prep, target enrichment, sequencing, and secondary analysis and will accept Variant Call File (VCF) and BAM (Binary Alignment/Map) files. It provides information on genomic variants based on published literature, public annotations, medical guidelines, drug labels and results of clinical trials. The software reports a tiered classification based on modified AMP guidelines, to aid in interpretation of detected variants, inform available therapies, and create a report. To validate accuracy and reproducibility of the NMP software and curation process when used by the intended users, a usability study was performed. Methods: 15 VCF files were prepared, including 12 semi-contrived VCF files across 4 different solid tumor types (3 lung, 3 colon, 3 melanoma and 3 breast). Each file contained on average 8 variants, 4 AMP Tier I variants (strong clinical significance) and 4 non-Tier I variants including SNVs, Indels, Fusions and CNVs. In addition, each case had filtered out variants (based on a variant allele frequency (VAF) &amp;lt;1% or a read depth &amp;lt; 500) with 1 case containing ~9000 and 2 cases containing ~500 filtered out variants. There were 3 VCF files designed to create error messages (1 &amp;gt; 10,000 variants, 1 VAF filter value missing, 1 incorrect reference genome). The study was performed at 3 external sites with 1, 2, and 3 users (total 6 users). Users downloaded the files onto their computers and processed them according to the instructions provided. Results: Correct variant call lists 100% (486/486), variant call list after filter modification 100% (42/42). Most critical was user agreement of Tier classification (Tier I vs. non-Tier I) for a pre-defined filter set: 99.6% (484/486). One user reclassified a MET amplification (lung case) from Tier I to Tier II and one user reclassified a BRAF V600D mutation (colon case) from Tier II to Tier I. In addition, the three cases designed to produce error messages all failed NMP processing: 100% (18/18). Conclusions: NAVIFY® Mutation Profiler is a robust automated solution for variant reporting. The annotation, curation and interpretation provided is highly concordant with molecular genetics experts. With the increasing number of known clinically relevant variants, software capable of automatically identifying and accurately interpreting variants promises to decrease the manual review time necessary to account for and inform on relevant variants. Citation Format: Sidney Alexander Scudder, Anoop Grewal, Lisha Capucion, Guili Zhang, Leonid Formin, Shuba Krishna, Xi Decker, Joanie Chung. Clinical validation of NAVIFY® Mutation Profiler for solid tumor NGS variant interpretation [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5456.