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Cited by 199

The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

A Decision Support Framework for Genomically Informed Investigational Cancer Therapy

Open access
Meric-Bernstam, Funda, Johnson, Amber, Holla, Vijaykumar, Bailey, Ann Marie, Brusco, Lauren, Chen, Ken, Routbort, Mark, Patel, Keyur P., Zeng, Jia, Kopetz, Scott, Davies, Michael A., Piha-Paul, Sarina A., Hong, David S., Eterovic, Agda Karina, Tsimberidou, Apostolia M., Broaddus, Russell, Bernstam, Elmer V., Shaw, Kenna R., Mendelsohn, John, Mills, Gordon B.·2015·JNCI: Journal of the National Cancer Institute

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.

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Metadata

Authors
Meric-Bernstam, F., Johnson, A., Holla, V., Bailey, A. M., Brusco, L., Chen, K., Routbort, M., Patel, K. P., Zeng, J., Kopetz, S., Davies, M. A., Piha-Paul, S. A., Hong, D. S., Eterovic, A. K., Tsimberidou, A. M., Broaddus, R., Bernstam, E. V., Shaw, K. R., Mendelsohn, J., & Mills, G. B.
Venue
JNCI: Journal of the National Cancer Institute
Published
2015-04-11
Volume
107
Issue
7
ISSN
  • 0027-8874 (ISSN-L)
  • 1460-2105
OpenAlex
W2026455681
Cited by
199
References
12
FWCI
9.91
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: A Decision Support Framework for Genomically Informed Investigational Cancer Therapy. https://app.cochat.ai/papers/10.1093/jnci/djv098
The paper
Meric-Bernstam, F., Johnson, A., Holla, V., Bailey, A. M., Brusco, L., Chen, K., Routbort, M., Patel, K. P., Zeng, J., Kopetz, S., Davies, M. A., Piha-Paul, S. A., Hong, D. S., Eterovic, A. K., Tsimberidou, A. M., Broaddus, R., Bernstam, E. V., Shaw, K. R., Mendelsohn, J., & Mills, G. B. (2015). A Decision Support Framework for Genomically Informed Investigational Cancer Therapy. JNCI: Journal of the National Cancer Institute. https://doi.org/10.1093/jnci/djv098

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.