Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors |
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Authors: | Alan J. Fox Matthew C. Hiemenz David B. Lieberman Shrey Sukhadia Barnett Li Joseph Grubb Patrick Candrea Karthik Ganapathy Jianhua Zhao David Roth Evan Alley Alison Loren Jennifer J. D. Morrissette |
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Affiliation: | 1Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania;2Division of Hematology/Oncology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania;3Abramson Cancer Center |
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Abstract: | As our understanding of the driver mutations necessary for initiation and progression of cancers improves, we gain critical information on how specific molecular profiles of a tumor may predict responsiveness to therapeutic agents or provide knowledge about prognosis. At our institution a tumor genotyping program was established as part of routine clinical care, screening both hematologic and solid tumors for a wide spectrum of mutations using two next-generation sequencing (NGS) panels: a custom, 33 gene hematological malignancies panel for use with peripheral blood and bone marrow, and a commercially produced solid tumor panel for use with formalin-fixed paraffin-embedded tissue that targets 47 genes commonly mutated in cancer. Our workflow includes a pathologist review of the biopsy to ensure there is adequate amount of tumor for the assay followed by customized DNA extraction is performed on the specimen. Quality control of the specimen includes steps for quantity, quality and integrity and only after the extracted DNA passes these metrics an amplicon library is generated and sequenced. The resulting data is analyzed through an in-house bioinformatics pipeline and the variants are reviewed and interpreted for pathogenicity. Here we provide a snapshot of the utility of each panel using two clinical cases to provide insight into how a well-designed NGS workflow can contribute to optimizing clinical outcomes. |
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Keywords: | Cancer Research Issue 115 Cancer Biology Oncology massively parallel sequencing acute myeloid leukemia lung adenocarcinoma bioinformatics targeted therapy allelic frequency activating mutation prognostic |
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