A Decision Support Framework for Genomically Informed Investigational Cancer Therapy

Funda Meric‐Bernstam(The University of Texas MD Anderson Cancer Center), Amber M. Johnson(The University of Texas MD Anderson Cancer Center), Vijaykumar Holla(The University of Texas MD Anderson Cancer Center), Ann M. Bailey(The University of Texas MD Anderson Cancer Center), Lauren Brusco(The University of Texas MD Anderson Cancer Center), Ken Chen(The University of Texas MD Anderson Cancer Center), Mark J. Routbort(The University of Texas MD Anderson Cancer Center), Keyur P. Patel(The University of Texas MD Anderson Cancer Center), Jia Zeng(The University of Texas MD Anderson Cancer Center), Scott Kopetz(The University of Texas MD Anderson Cancer Center), Michael A. Davies(The University of Texas MD Anderson Cancer Center), Sarina A. Piha‐Paul(The University of Texas MD Anderson Cancer Center), David S. Hong(The University of Texas MD Anderson Cancer Center), Agda Karina Eterovic(The University of Texas MD Anderson Cancer Center), Apostolia M. Tsimberidou(The University of Texas MD Anderson Cancer Center), Russell Broaddus(The University of Texas MD Anderson Cancer Center), Elmer V. Bernstam(The University of Texas MD Anderson Cancer Center), Kenna Shaw(The University of Texas MD Anderson Cancer Center), John Mendelsohn(The University of Texas MD Anderson Cancer Center), Gordon B. Mills(The University of Texas MD Anderson Cancer Center)
JNCI Journal of the National Cancer Institute
April 11, 2015
Cited by 203Open Access
Full Text

Abstract

Rapidly 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.


Related Papers

No related papers found

Powered by citation graph analysis