Title |
A Functional Cancer Genomics Screen Identifies a Druggable Synthetic Lethal Interaction between MSH3 and PRKDC
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Published in |
Cancer Discovery, May 2014
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DOI | 10.1158/2159-8290.cd-13-0907 |
Pubmed ID | |
Authors |
Felix Dietlein, Lisa Thelen, Mladen Jokic, Ron D. Jachimowicz, Laura Ivan, Gero Knittel, Uschi Leeser, Johanna van Oers, Winfried Edelmann, Lukas C. Heukamp, H. Christian Reinhardt |
Abstract |
Here, we use a large-scale cell line-based approach to identify cancer cell-specific mutations that are associated with DNA-dependent protein kinase catalytic subunit (DNA-PKcs) dependence. For this purpose, we profiled the mutational landscape across 1,319 cancer-associated genes of 67 distinct cell lines and identified numerous genes involved in homologous recombination-mediated DNA repair, including BRCA1, BRCA2, ATM, PAXIP, and RAD50, as being associated with non-oncogene addiction to DNA-PKcs. Mutations in the mismatch repair gene MSH3, which have been reported to occur recurrently in numerous human cancer entities, emerged as the most significant predictors of DNA-PKcs addiction. Concordantly, DNA-PKcs inhibition robustly induced apoptosis in MSH3-mutant cell lines in vitro and displayed remarkable single-agent efficacy against MSH3-mutant tumors in vivo. Thus, we here identify a therapeutically actionable synthetic lethal interaction between MSH3 and the non-homologous end joining kinase DNA-PKcs. Our observations recommend DNA-PKcs inhibition as a therapeutic concept for the treatment of human cancers displaying homologous recombination defects. |
X Demographics
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 2 | 2% |
China | 1 | <1% |
Brazil | 1 | <1% |
Unknown | 103 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 24 | 22% |
Student > Ph. D. Student | 22 | 21% |
Student > Bachelor | 11 | 10% |
Professor > Associate Professor | 8 | 7% |
Student > Doctoral Student | 6 | 6% |
Other | 14 | 13% |
Unknown | 22 | 21% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 34 | 32% |
Biochemistry, Genetics and Molecular Biology | 25 | 23% |
Medicine and Dentistry | 15 | 14% |
Immunology and Microbiology | 2 | 2% |
Economics, Econometrics and Finance | 1 | <1% |
Other | 3 | 3% |
Unknown | 27 | 25% |