TY - JOUR
T1 - Next-Generation Sequencing and Result Interpretation in Clinical Oncology
T2 - Challenges of Personalized Cancer Therapy
AU - Khotskaya, Yekaterina B.
AU - Mills, Gordon B.
AU - Mills Shaw, Kenna R.
N1 - Publisher Copyright:
© 2017 by Annual Reviews.
PY - 2017/1/14
Y1 - 2017/1/14
N2 - 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.
AB - 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.
KW - Decision support
KW - Driver mutations
KW - Passenger mutations
KW - Variant actionability
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U2 - 10.1146/annurev-med-102115-021556
DO - 10.1146/annurev-med-102115-021556
M3 - Article
C2 - 27813876
AN - SCOPUS:85009956018
SN - 0066-4219
VL - 68
SP - 113
EP - 125
JO - Annual review of medicine
JF - Annual review of medicine
ER -