Cited by 645Lung Cancer Treatments and MutationsCancer Genomics and DiagnosticsLung Cancer Diagnosis and Treatment

The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.

Prospective Comprehensive Molecular Characterization of Lung Adenocarcinomas for Efficient Patient Matching to Approved and Emerging Therapies

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Published version of a preprint

Abstract

Tumor genetic testing is standard of care for patients with advanced lung adenocarcinoma, but the fraction of patients who derive clinical benefit remains undefined. Here, we report the experience of 860 patients with metastatic lung adenocarcinoma analyzed prospectively for mutations in >300 cancer-associated genes. Potentially actionable genetic events were stratified into one of four levels based upon published clinical or laboratory evidence that the mutation in question confers increased sensitivity to standard or investigational therapies. Overall, 37.1% (319/860) of patients received a matched therapy guided by their tumor molecular profile. Excluding alterations associated with standard-of-care therapy, 14.4% (69/478) received matched therapy, with a clinical benefit of 52%. Use of matched therapy was strongly influenced by the level of preexistent clinical evidence that the mutation identified predicts for drug response. Analysis of genes mutated significantly more often in tumors without known actionable mutations nominated STK11 and KEAP1 as possible targetable mitogenic drivers. Significance: An increasing number of therapies that target molecular alterations required for tumor maintenance and progression have demonstrated clinical activity in patients with lung adenocarcinoma. The data reported here suggest that broader, early testing for molecular alterations that have not yet been recognized as standard-of-care predictive biomarkers of drug response could accelerate the development of targeted agents for rare mutational events and could result in improved clinical outcomes. Cancer Discov; 7(6); 596–609. ©2017 AACR. See related commentary by Liu et al., p. 555. This article is highlighted in the In This Issue feature, p. 539

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  1. OncoKB.org, 2016, Precision Oncology Knowledge Base [Internet]
  2. Banno, 2016, : 10.1111/.12980, Sensitivities to various EGFR-TKIs of uncommon EGFR mutations L861Q and S768I: what is the optimal EGFR-TKI?, Cancer Sci · DOI

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Metadata

Authors
Jordan, E. J., Kim, H. R., Arcila, M. E., Barron, D., Chakravarty, D., Gao, J., Chang, M. T., Ni, A., Kundra, R., Jonsson, P., Jayakumaran, G., Gao, S. P., Johnsen, H. C., Hanrahan, A. J., Zehir, A., Rekhtman, N., Ginsberg, M. S., Li, B. T., Yu, H. A., Paik, P. K., Drilon, A., Hellmann, M. D., Reales, D. N., Benayed, R., Rusch, V. W., Kris, M. G., Chaft, J. E., Baselga, J., Taylor, B. S., Schultz, N., Rudin, C. M., Hyman, D. M., Berger, M. F., Solit, D. B., Ladanyi, M., & Riely, G. J.
Affiliations
  • Memorial Sloan Kettering Cancer Center (US)
  • 6Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York.
  • 1Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
Corresponding author
Riely, Gregory J.
Venue
Cancer Discovery
Published
2017-06-01
Volume
7
Issue
6
Pages
596-609
ISSN
  • 2159-8274 (ISSN-L)
  • 2159-8290
OpenAlex
W2603411876
Cited by
643
References
49
Citations by year
2026: 30 · 2025: 40 · 2024: 65 · 2023: 99 · 2022: 94 · 2021: 101 · 2020: 79 · 2019: 65 · 2018: 55 · 2017: 12
FWCI
47.73
Type
journal article
Language
en
Open access
Locations
  • Cancer Discovery (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Institutes of Health (UL1TR002384)
  • National Cancer Institute (P30CA008748)
  • National Center for Advancing Translational Sciences
Topics
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
Keywords
lung adenocarcinoma, metastatic lung cancer, actionable mutations, targeted therapy, predictive biomarkers, drug response, STK11, Keap1, clinical benefit, molecular profiling
MeSH terms
Adenocarcinoma of Lung, Adenocarcinoma, Adolescent, Adult, Aged, Female, Genetic Testing, Humans, Lung Neoplasms, Male, Middle Aged, Mutation, Biomarkers, Tumor, Young Adult, Molecular Targeted Therapy

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