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Actionability classification of variants of unknown significance correlates with functional effect

Amber M. Johnson, Patrick Kwok‐Shing Ng, Michael Kahle, J. Castillo, Bianca Amador, Yujia Wang, Jia Zeng, Vijaykumar Holla, Thuy M. Vu, Fei Su, Sun‐Hee Kim, Tara Conway, Xianli Jiang, Ken Chen, Kenna Shaw, Timothy A. Yap, Jordi Rodón, Gordon B. Mills, Funda Meric‐Bernstam

2023npj Precision Oncology14 citationsDOIOpen Access PDF

Abstract

Genomically-informed therapy requires consideration of the functional impact of genomic alterations on protein expression and/or function. However, a substantial number of variants are of unknown significance (VUS). The MD Anderson Precision Oncology Decision Support (PODS) team developed an actionability classification scheme that categorizes VUS as either "Unknown" or "Potentially" actionable based on their location within functional domains and/or proximity to known oncogenic variants. We then compared PODS VUS actionability classification with results from a functional genomics platform consisting of mutant generation and cell viability assays. 106 (24%) of 438 VUS in 20 actionable genes were classified as oncogenic in functional assays. Variants categorized by PODS as Potentially actionable (N = 204) were more likely to be oncogenic than those categorized as Unknown (N = 230) (37% vs 13%, p = 4.08e-09). Our results demonstrate that rule-based actionability classification of VUS can identify patients more likely to have actionable variants for consideration with genomically-matched therapy.

Topics & Concepts

Functional genomicsClassification schemeComputational biologyGenomicsBioinformaticsMedicineGeneBiologyGeneticsGenomeComputer scienceMachine learningCancer Genomics and DiagnosticsGenomics and Rare DiseasesCRISPR and Genetic Engineering