Title |
Targeted genetic dependency screen facilitates identification of actionable mutations in FGFR4, MAP3K9, and PAK5 in lung cancer
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Published in |
Proceedings of the National Academy of Sciences of the United States of America, July 2013
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DOI | 10.1073/pnas.1305207110 |
Pubmed ID | |
Authors |
Shameem Fawdar, Eleanor W. Trotter, Yaoyong Li, Natalie L. Stephenson, Franziska Hanke, Anna A. Marusiak, Zoe C. Edwards, Sara Ientile, Bohdan Waszkowycz, Crispin J. Miller, John Brognard |
Abstract |
Approximately 70% of patients with non-small-cell lung cancer present with late-stage disease and have limited treatment options, so there is a pressing need to develop efficacious targeted therapies for these patients. This remains a major challenge as the underlying genetic causes of ~50% of non-small-cell lung cancers remain unknown. Here we demonstrate that a targeted genetic dependency screen is an efficient approach to identify somatic cancer alterations that are functionally important. By using this approach, we have identified three kinases with gain-of-function mutations in lung cancer, namely FGFR4, MAP3K9, and PAK5. Mutations in these kinases are activating toward the ERK pathway, and targeted depletion of the mutated kinases inhibits proliferation, suppresses constitutive activation of downstream signaling pathways, and results in specific killing of the lung cancer cells. Genomic profiling of patients with lung cancer is ushering in an era of personalized medicine; however, lack of actionable mutations presents a significant hurdle. Our study indicates that targeted genetic dependency screens will be an effective strategy to elucidate somatic variants that are essential for lung cancer cell viability. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 6 | 35% |
United Kingdom | 3 | 18% |
Ireland | 1 | 6% |
Peru | 1 | 6% |
Canada | 1 | 6% |
Belgium | 1 | 6% |
Unknown | 4 | 24% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 12 | 71% |
Science communicators (journalists, bloggers, editors) | 2 | 12% |
Practitioners (doctors, other healthcare professionals) | 2 | 12% |
Scientists | 1 | 6% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 1% |
India | 1 | 1% |
Germany | 1 | 1% |
Unknown | 80 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 24 | 29% |
Student > Ph. D. Student | 19 | 23% |
Student > Bachelor | 7 | 8% |
Professor > Associate Professor | 6 | 7% |
Other | 4 | 5% |
Other | 11 | 13% |
Unknown | 12 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 29 | 35% |
Biochemistry, Genetics and Molecular Biology | 21 | 25% |
Medicine and Dentistry | 12 | 14% |
Chemistry | 5 | 6% |
Computer Science | 1 | 1% |
Other | 5 | 6% |
Unknown | 10 | 12% |