Nikita Mehta1, Rong He2, David S Viswanatha3. 1. Department of Laboratory Medicine and Pathology, Molecular Hematology Laboratory, Mayo Clinic, Rochester, MN, USA. MehtaN5@mskcc.org. 2. Department of Laboratory Medicine and Pathology, Molecular Hematology Laboratory, Mayo Clinic, Rochester, MN, USA. 3. Department of Laboratory Medicine and Pathology, Molecular Hematology Laboratory, Mayo Clinic, Rochester, MN, USA. Viswanatha.David@mayo.edu.
Abstract
INTRODUCTION: Accurate classification of somatic genetic alterations detected by next-generation sequencing (NGS) assays is of paramount importance to ensure the provision of high-quality clinical data. Clinical significance of variants can be assessed and tiered based on guidelines from the Association for Molecular Pathology (AMP), the American Society of Clinical Oncology, and the College of American Pathology for the interpretation of somatic sequence variants identified in cancer. METHODS: We sought to develop a formal structured approach for the classification of somatic variants in hematologic neoplasms, to account for both a variant's clinical significance and its ability to drive tumorigenesis, by adapting elements from these existing guidelines. However, we additionally utilized key criteria from the American College of Medical Genetics/AMP standards for variant reporting to focus evaluation into specific categories of evidence and to gauge the effect of a given variant on tumorigenesis. RESULTS: The combined approach was applied to the annotation of 87 variants identified by a targeted NGS panel for myeloid neoplasms. In the application of our variant evaluation, we classified 2/87 variants as benign, 6/87 as likely benign, 56/87 as variants of unknown significance (VUS), 13/87 variants as likely pathogenic, and 10/87 variants as pathogenic. CONCLUSION: Well-established oncogenic alterations were accurately classified as pathogenic. Although there is no defined benchmark for the remaining variants, drawing from two existing guidelines enabled the creation of a modified curation process for variant interpretation that emphasizes systematic review of relevant evidence.
INTRODUCTION: Accurate classification of somatic genetic alterations detected by next-generation sequencing (NGS) assays is of paramount importance to ensure the provision of high-quality clinical data. Clinical significance of variants can be assessed and tiered based on guidelines from the Association for Molecular Pathology (AMP), the American Society of Clinical Oncology, and the College of American Pathology for the interpretation of somatic sequence variants identified in cancer. METHODS: We sought to develop a formal structured approach for the classification of somatic variants in hematologic neoplasms, to account for both a variant's clinical significance and its ability to drive tumorigenesis, by adapting elements from these existing guidelines. However, we additionally utilized key criteria from the American College of Medical Genetics/AMP standards for variant reporting to focus evaluation into specific categories of evidence and to gauge the effect of a given variant on tumorigenesis. RESULTS: The combined approach was applied to the annotation of 87 variants identified by a targeted NGS panel for myeloid neoplasms. In the application of our variant evaluation, we classified 2/87 variants as benign, 6/87 as likely benign, 56/87 as variants of unknown significance (VUS), 13/87 variants as likely pathogenic, and 10/87 variants as pathogenic. CONCLUSION: Well-established oncogenic alterations were accurately classified as pathogenic. Although there is no defined benchmark for the remaining variants, drawing from two existing guidelines enabled the creation of a modified curation process for variant interpretation that emphasizes systematic review of relevant evidence.
Authors: Mithun Vinod Shah; Abhishek A Mangaonkar; Kebede H Begna; Hassan B Alkhateeb; Patricia Greipp; Ahmad Nanaa; Michelle A Elliott; William J Hogan; Mark R Litzow; Kristen McCullough; Ayalew Tefferi; Naseema Gangat; Mrinal M Patnaik; Aref Al-Kali; Rong He; Dong Chen Journal: Blood Cancer J Date: 2022-07-08 Impact factor: 9.812