Mahadeo A Sukhai1,2, Kenneth J Craddock1,2, Mariam Thomas1,2, Aaron R Hansen3,2, Tong Zhang1,2, Lillian Siu3,2, Philippe Bedard3,2, Tracy L Stockley1,4,2, Suzanne Kamel-Reid1,4,2. 1. Laboratory Medicine Program, Advanced Molecular Diagnostics Laboratory, Department of Pathology, University Health Network, Toronto, Ontario, Canada. 2. Cancer Genomics Program, Princess Margaret Cancer Centre, The University Health Network, Toronto, Ontario, Canada. 3. Division of Medical Oncology, Princess Margaret Cancer Centre, The University Health Network, Toronto, Ontario, Canada. 4. Department of Laboratory Medicine and Pathobiology, The University of Toronto, Toronto, Ontario, Canada.
Abstract
PURPOSE: Interpretation systems for clinical laboratory reporting of genetic variants for inherited conditions have been widely published. By contrast, there are no existing systems for interpretation and classification of somatic variants found from molecular testing of cancer. METHODS: We designed an assessment protocol and classification system for somatic variants identified through next-generation sequencing molecular profiling of tumor-derived samples and applied these to a pilot dataset of somatic variants found by next-generation sequencing profiling of 158 tumor samples derived from advanced cancer patients examined at the Princess Margaret Cancer Centre. RESULTS: We present a classification system to interpret the significance of genetic variants in molecular analysis of cancer, including the following key factors: (i) known or predicted pathogenicity of the variant; (ii) primary site and tumor histology in which the variant is found; (iii) recurrence of the variant; and (iv) evidence of clinical actionability. We used these factors to develop a five-category somatic variant classification for simplified reporting of variant interpretations to treating oncologists. CONCLUSION: Our somatic variant classification can be of practical value to other clinical molecular laboratories performing cancer genetic profiling by promoting consistent reporting of somatic variants and permitting harmonization of variant data among laboratories and clinical studies.
PURPOSE: Interpretation systems for clinical laboratory reporting of genetic variants for inherited conditions have been widely published. By contrast, there are no existing systems for interpretation and classification of somatic variants found from molecular testing of cancer. METHODS: We designed an assessment protocol and classification system for somatic variants identified through next-generation sequencing molecular profiling of tumor-derived samples and applied these to a pilot dataset of somatic variants found by next-generation sequencing profiling of 158 tumor samples derived from advanced cancer patients examined at the Princess Margaret Cancer Centre. RESULTS: We present a classification system to interpret the significance of genetic variants in molecular analysis of cancer, including the following key factors: (i) known or predicted pathogenicity of the variant; (ii) primary site and tumor histology in which the variant is found; (iii) recurrence of the variant; and (iv) evidence of clinical actionability. We used these factors to develop a five-category somatic variant classification for simplified reporting of variant interpretations to treating oncologists. CONCLUSION: Our somatic variant classification can be of practical value to other clinical molecular laboratories performing cancer genetic profiling by promoting consistent reporting of somatic variants and permitting harmonization of variant data among laboratories and clinical studies.
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