Next-Generation Sequencing and Result Interpretation in Clinical Oncology: Challenges of Personalized Cancer Therapy

The tools of next-generation sequencing (NGS) technology, such as targeted sequencing of candidate cancer genes and whole-exome and -genome sequencing, coupled with encouraging clinical results based on the use of targeted therapeutics and biomarker-guided clinical trials, are fueling further techno...

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Bibliographic Details
Published in:	Annual review of medicine Vol. 68; no. 1; pp. 113 - 125
Main Authors:	Khotskaya, Yekaterina B, Mills, Gordon B, Mills Shaw, Kenna R
Format:	Journal Article
Language:	English
Published:	United States Annual Reviews 14-01-2017 Annual Reviews, Inc
Subjects:	Biomarkers Cancer Clinical Decision-Making Clinical trials Decision making decision support driver mutations Drug Resistance - genetics Genes Germ-Line Mutation Humans Interdisciplinary Communication Medical Oncology Molecular Targeted Therapy Mutation Mutation - genetics Neoplasms - drug therapy Neoplasms - genetics Oncology passenger mutations Patient Care Team Precision Medicine Sequence Analysis, DNA - methods variant actionability Whole Genome Sequencing driver mutations variant actionability decision support passenger mutations
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Summary:	The tools of next-generation sequencing (NGS) technology, such as targeted sequencing of candidate cancer genes and whole-exome and -genome sequencing, coupled with encouraging clinical results based on the use of targeted therapeutics and biomarker-guided clinical trials, are fueling further technological advancements of NGS technology. However, NGS data interpretation is associated with challenges that must be overcome to promote the techniques' effective integration into clinical oncology practice. Specifically, sequencing of a patient's tumor often yields 30-65 somatic variants, but most of these variants are "passenger" mutations that are phenotypically neutral and thus not targetable. Therefore, NGS data must be interpreted by multidisciplinary decision-support teams to determine mutation actionability and identify potential "drivers," so that the treating physician can prioritize what clinical decisions can be pursued in order to provide cancer therapy that is personalized to the patient and his or her unique genome.
Bibliography:	ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-3 content type line 23 ObjectType-Review-1
ISSN:	0066-4219 1545-326X
DOI:	10.1146/annurev-med-102115-021556