Literature DB >> 32961319

Assessment of a Highly Curated Somatic Oncology Database to Aid in the Interpretation of Clinically Important Variants in Next-Generation Sequencing Results.

Stephanie J Yaung1, Shuba Krishna2, Liu Xi3, Christine Ju4, John F Palma5, Maximilian Schmid5.   

Abstract

This study evaluated the accuracy of NAVIFY Mutation Profiler, a cloud-based CE-IVD software that aids in interpreting clinically relevant variants detected in somatic oncology next-generation sequencing tests. This tool reports tiered classifications based on different levels of clinical evidence from a highly curated, regularly updated database derived from medical guidelines, drug approvals, and peer-reviewed literature. A retrospective analysis was performed on next-generation sequencing results from 37 lung cancer cases treated with chemotherapy (n = 10), EGFR tyrosine kinase inhibitor (TKI) (n = 5), or ALK TKI (n = 22). Several aspects were assessed, including accuracy of interpretation compared with manual curation, validity of curation content updates over time, and agreement with public databases. For chemotherapy cases with no targetable biomarkers, NAVIFY Mutation Profiler did not identify any targeted therapies. In EGFR and ALK TKI cases, the software associated appropriate targeted therapies and accurately interpreted variant combinations containing drug-resistance variants. Of the nine unique ALK mutations conferring resistance to crizotinib, NAVIFY Mutation Profiler provided correct annotation for all mutations, whereas OncoKB and Catalogue of Somatic Mutations in Cancer indicated crizotinib resistance for eight of nine mutations. For 145 variants analyzed, NAVIFY Mutation Profiler and OncoKB showed substantial agreement (Cohen κ = 0.62) for classifying actionable mutations. Furthermore, NAVIFY Mutation Profiler presented accurate targeted therapies across different regions and remained up-to-date with evolving regional approvals and medical guidelines.
Copyright © 2020 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

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Year:  2020        PMID: 32961319     DOI: 10.1016/j.jmoldx.2020.08.004

Source DB:  PubMed          Journal:  J Mol Diagn        ISSN: 1525-1578            Impact factor:   5.568


  2 in total

1.  An online compendium of treatable genetic disorders.

Authors:  David Bick; Sarah L Bick; David P Dimmock; Tom A Fowler; Mark J Caulfield; Richard H Scott
Journal:  Am J Med Genet C Semin Med Genet       Date:  2020-12-22       Impact factor: 3.908

2.  Liquid biopsy as an option for predictive testing and prognosis in patients with lung cancer.

Authors:  Alvida Qvick; Bianca Stenmark; Jessica Carlsson; Johan Isaksson; Christina Karlsson; Gisela Helenius
Journal:  Mol Med       Date:  2021-07-03       Impact factor: 6.354

  2 in total

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