In:
Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 38, No. 15_suppl ( 2020-05-20), p. e14072-e14072
Abstract:
e14072 Background: Evolving medical guidelines and complex multi-variant data from next-generation sequencing (NGS) testing of cancer samples make routine clinical interpretation of somatic variants challenging. We assessed the ability of NAVIFY(R) Mutation Profiler*, a CE-IVD somatic variant interpretation tool, to yield accurate time- and geography-specific clinical content on 2511 samples from The Cancer Genome Atlas (TCGA) across six solid tumor types. Methods: Whole exomes from lung adenocarcinoma (n = 469), lung squamous cell carcinoma (n = 325), colon adenocarcinoma (n = 368), rectum adenocarcinoma (n = 149), breast invasive carcinoma (n = 806), and skin cutaneous melanoma (n = 394) cases were analyzed. We utilized TCGA data from the Multi-Center Mutation Calling in Multiple Cancers (MC3) project to obtain consensus calling results of single nucleotide variants and indels. The open-access Mutation Annotation Format (MAF) file (v0.2.8) that stores variant calls was lifted to human reference genome GRCh38 and converted to individual Variant Call Format (VCF) files per case. VCF files were uploaded to NAVIFY Mutation Profiler to interpret actionable mutations according to a highly curated and up-to-date knowledge base (Roche Content v2.13.0 released December 6, 2019). We further assessed the accuracy of interpreting co-occurrences of actionable mutations. Results: Over 1.24 million somatic mutations across 20,590 genes were assessed with NAVIFY Mutation Profiler, which reported tier classifications of variants based on consensus recommendations from AMP, ASCO, CAP, and ACMG. 86% of cases had variants of strong (Tier I-A or I-B) or potential (Tier II-C or II-D) clinical significance; 56% of these cases had Tier I classifications, supported by robust clinical evidence. Potentially actionable variant-variant interactions were found in 14% of cases. The tool also identified appropriate tier classifications by geographic region in accordance with local medical guidelines. Conclusions: To benchmark against other tools, we utilized available exome data from TCGA MC3 to assess NAVIFY Mutation Profiler. While this study likely underestimates the fraction of cases with actionable mutations, given that copy number alterations or rearrangements are also present in TCGA samples, we found a higher yield of potentially actionable annotation than other published methods. * This product has not been evaluated by the Food and Drug Administration and is not commercially available in the United States.
Type of Medium:
Online Resource
ISSN:
0732-183X
,
1527-7755
DOI:
10.1200/JCO.2020.38.15_suppl.e14072
Language:
English
Publisher:
American Society of Clinical Oncology (ASCO)
Publication Date:
2020
detail.hit.zdb_id:
2005181-5
