Title |
High-Order Drug Combinations Are Required to Effectively Kill Colorectal Cancer Cells
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Published in |
Cancer Research, November 2016
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DOI | 10.1158/0008-5472.can-15-3425 |
Pubmed ID | |
Authors |
Thomas Horn, Stéphane Ferretti, Nicolas Ebel, Angela Tam, Samuel Ho, Fred Harbinski, Ali Farsidjani, Matthew Zubrowski, William R Sellers, Robert Schlegel, Dale Porter, Erick Morris, Jens Wuerthner, Sébastien Jeay, Joel Greshock, Ensar Halilovic, Levi A Garraway, Giordano Caponigro, Joseph Lehár |
Abstract |
Like classical chemotherapy regimens used to treat cancer, targeted therapies will also rely upon polypharmacology, but tools are still lacking to predict which combinations of molecular-targeted drugs may be most efficacious. In this study, we used image-based proliferation and apoptosis assays in colorectal cancer cell lines to systematically investigate the efficacy of combinations of two to six drugs which target critical oncogenic pathways. Drug pairs targeting key signaling pathways resulted in synergies across a broad spectrum of genetic backgrounds, but often yielded only cytostatic responses. Enhanced cytotoxicity was observed when additional processes including apoptosis and cell cycle were targeted as part of the combination. In some cases, where cell lines were resistant to paired and tripled drugs, increased expression of anti-apoptotic proteins was observed, requiring a fourth-order combination to induce cytotoxicity. Our results illustrate how high-order drug combinations are needed to kill drug-resistant cancer cells, and they also show how systematic drug combination screening together with a molecular understanding of drug responses may help define optimal cocktails to overcome aggressive cancers. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 8 | 50% |
France | 1 | 6% |
United Kingdom | 1 | 6% |
Unknown | 6 | 38% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 10 | 63% |
Scientists | 4 | 25% |
Practitioners (doctors, other healthcare professionals) | 2 | 13% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Netherlands | 1 | 1% |
Unknown | 70 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 21 | 30% |
Student > Ph. D. Student | 12 | 17% |
Student > Bachelor | 5 | 7% |
Other | 5 | 7% |
Student > Master | 5 | 7% |
Other | 11 | 15% |
Unknown | 12 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 24 | 34% |
Agricultural and Biological Sciences | 11 | 15% |
Medicine and Dentistry | 7 | 10% |
Pharmacology, Toxicology and Pharmaceutical Science | 4 | 6% |
Mathematics | 2 | 3% |
Other | 8 | 11% |
Unknown | 15 | 21% |