• Funda Meric-Bernstam, Amber Johnson, Vijaykumar Holla, Ann Marie Bailey, Lauren Brusco, Ken Chen, Mark Routbort, Keyur P Patel, Jia Zeng, Scott Kopetz, Michael A Davies, Sarina A Piha-Paul, David S Hong, Agda Karina Eterovic, Apostolia M Tsimberidou, Russell Broaddus, Elmer V Bernstam, Kenna R Shaw, John Mendelsohn, and Gordon B Mills.
• Sheikh Khalifa Al Nahyan Ben Zayed Institute for Personalized Cancer Therapy , the University of Texas MD Anderson Cancer Center, Houston, TX (FMB, AJ, VH, AMB, JZ, KRS, JM, GBM); Departments of Investigational Cancer Therapeutics (FMB, LB, SAPP, DSH, AMT), Surgical Oncology (FMB), Hematopathology (MR, KPP), Bioinformatics & Computational Biology (KC), GI Medical Oncology (SK), Melanoma Medical Oncology (MAD), Experimental Therapeutics (RB), Systems Biology (AKE, GBM), the University of Texas MD Anderson Cancer Center, Houston, TX; School of Biomedical Informatics, the University of Texas Health Science Center, Houston, TX (EVB). fmeric@mdanderson.org.
• J. Natl. Cancer Inst. 2015 Jul 1; 107 (7).

AbstractRapidly improving understanding of molecular oncology, emerging novel therapeutics, and increasingly available and affordable next-generation sequencing have created an opportunity for delivering genomically informed personalized cancer therapy. However, to implement genomically informed therapy requires that a clinician interpret the patient's molecular profile, including molecular characterization of the tumor and the patient's germline DNA. In this Commentary, we review existing data and tools for precision oncology and present a framework for reviewing the available biomedical literature on therapeutic implications of genomic alterations. Genomic alterations, including mutations, insertions/deletions, fusions, and copy number changes, need to be curated in terms of the likelihood that they alter the function of a "cancer gene" at the level of a specific variant in order to discriminate so-called "drivers" from "passengers." Alterations that are targetable either directly or indirectly with approved or investigational therapies are potentially "actionable." At this time, evidence linking predictive biomarkers to therapies is strong for only a few genomic markers in the context of specific cancer types. For these genomic alterations in other diseases and for other genomic alterations, the clinical data are either absent or insufficient to support routine clinical implementation of biomarker-based therapy. However, there is great interest in optimally matching patients to early-phase clinical trials. Thus, we need accessible, comprehensive, and frequently updated knowledge bases that describe genomic changes and their clinical implications, as well as continued education of clinicians and patients.© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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