Title |
Prospective Comprehensive Molecular Characterization of Lung Adenocarcinomas for Efficient Patient Matching to Approved and Emerging Therapies
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Published in |
Cancer Discovery, June 2017
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DOI | 10.1158/2159-8290.cd-16-1337 |
Pubmed ID | |
Authors |
Emmet J Jordan, Hyunjae R Kim, Maria E Arcila, David Barron, Debyani Chakravarty, JianJiong Gao, Matthew T Chang, Andy Ni, Ritika Kundra, Philip Jonsson, Gowtham Jayakumaran, Sizhi Paul Gao, Hannah C Johnsen, Aphrothiti J Hanrahan, Ahmet Zehir, Natasha Rekhtman, Michelle S Ginsberg, Bob T Li, Helena A Yu, Paul K Paik, Alexander Drilon, Matthew D Hellmann, Dalicia N Reales, Ryma Benayed, Valerie W Rusch, Mark G Kris, Jamie E Chaft, José Baselga, Barry S Taylor, Nikolaus Schultz, Charles M Rudin, David M Hyman, Michael F Berger, David B Solit, Marc Ladanyi, Gregory J Riely |
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 pre-existent 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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 25 | 49% |
Canada | 3 | 6% |
United Kingdom | 3 | 6% |
Germany | 2 | 4% |
Japan | 1 | 2% |
India | 1 | 2% |
Brazil | 1 | 2% |
Venezuela, Bolivarian Republic of | 1 | 2% |
Australia | 1 | 2% |
Other | 2 | 4% |
Unknown | 11 | 22% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 22 | 43% |
Members of the public | 21 | 41% |
Practitioners (doctors, other healthcare professionals) | 7 | 14% |
Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | <1% |
Czechia | 1 | <1% |
Unknown | 353 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 67 | 19% |
Student > Ph. D. Student | 50 | 14% |
Other | 32 | 9% |
Student > Master | 25 | 7% |
Student > Bachelor | 17 | 5% |
Other | 50 | 14% |
Unknown | 114 | 32% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 98 | 28% |
Biochemistry, Genetics and Molecular Biology | 78 | 22% |
Agricultural and Biological Sciences | 25 | 7% |
Computer Science | 5 | 1% |
Engineering | 5 | 1% |
Other | 24 | 7% |
Unknown | 120 | 34% |