Abstract 249: Comparison of variant classification between molecular diagnostics experts and decision support software
Authors: Stephanie J. Yaung, Shuba Krishna, Sidney Scudder, Maximilian Schmid, John F. Palma
Journal: Cancer Research (2021)

Abstract INTRODUCTION: Assessing the actionability of variants identified in next-generation sequencing (NGS) of solid tumors is challenging. Recommendations from AMP/ASCO/CAP/ACMG (Li et al. JMD 2017) provide guidelines for prioritizing variants based on clinical significance and actionability. Sirohi et al. (JMD 2020) reported on interrater agreement with the AMP guidelines by distributing 51 variants from solid tumor NGS to 20 participants at 10 US academic molecular diagnostics laboratories. Initial agreement based on independent assessment amongst the 20 experts was fair (Cohen κ = 0.35). To explore the potential for decision support software to streamline interpretation and improve the reliability of tier classification, we evaluated the same variants with NAVIFY® Mutation Profiler*, a CE-IVD somatic variant interpretation tool that automatically assigns tiers based on curated public evidence. METHODS: Reverse annotation from protein or coding sequence changes was completed with TransVar (Zhou et al. Nat Methods 2015) to obtain hg38 genomic coordinates for the 51 variants. Variants were prepared in VCF files and uploaded to NAVIFY Mutation Profiler (v2.0.0.22e0193) for analysis. The software assigned tier classifications using evidence in Roche curation content version 2.33.0 (released Nov 10, 2020). The default tier for each variant was compared to the tier assigned by the most experts in Sirohi et al. If there was a tie, the higher tier was used for comparison (e.g. Tier II when there was a tie between Tier II and III). RESULTS: There was good agreement (Cohen κ = 0.61) in tier assignments for 37 variants with curation content in NAVIFY Mutation Profiler compared to consensus expert curation in Sirohi et al. Most disagreements could be explained by emerging biomedical evidence, such as phase II clinical trial results for NFE2L2 in squamous cell lung carcinoma, or recommendations in NCCN guidelines. For example, ERBB2 mutations were up-classified by NAVIFY Mutation Profiler to Tier I due to NCCN therapy recommendations, including trastuzumab in combination with lapatinib or pertuzumab for ERBB2-amplified colorectal cancer and trastuzumab emtansine for non-small cell lung cancer with ERBB2 exon 20 insertions. Of the 14 variants without curation in the database, none were actionable, and the experts had classified 11 as Tier III and 3 as Tier II. CONCLUSIONS: When curation content was available, there was high agreement between the assigned tier in NAVIFY Mutation Profiler and the most common tier assigned by 20 molecular diagnostics experts in a previously published study. The continuous growth in new biomedical evidence requires staying current with the latest guidelines and clinical trial results, or the use of regularly updated databases, to accurately interpret somatic cancer variants from NGS test results. * This product is for Research Use Only; Not for use in diagnostic procedures in the US. Citation Format: Stephanie J. Yaung, Shuba Krishna, Sidney Scudder, Maximilian Schmid, John F. Palma. Comparison of variant classification between molecular diagnostics experts and decision support software [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 249.