An unbiased oncology compound screen to identify novel combination strategies
Published version of a preprint
Abstract
Combination drug therapy is a widely used paradigm for managing numerous human malignancies. In cancer treatment, additive and/or synergistic drug combinations can convert weakly efficacious monotherapies into regimens that produce robust antitumor activity. This can be explained in part through pathway interdependencies that are critical for cancer cell proliferation and survival. However, identification of the various interdependencies is difficult due to the complex molecular circuitry that underlies tumor development and progression. Here, we present a high-throughput platform that allows for an unbiased identification of synergistic and efficacious drug combinations. In a screen of 22,737 experiments of 583 doublet combinations in 39 diverse cancer cell lines using a 4 by 4 dosing regimen, both well-known and novel synergistic and efficacious combinations were identified. Here, we present an example of one such novel combination, a Wee1 inhibitor (AZD1775) and an mTOR inhibitor (ridaforolimus), and demonstrate that the combination potently and synergistically inhibits cancer cell growth in vitro and in vivo. This approach has identified novel combinations that would be difficult to reliably predict based purely on our current understanding of cancer cell biology. Mol Cancer Ther; 15(6); 1155–62. ©2016 AACR.
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Most in vivo synergy studies simply compare tumor volume at a single day using t test, or use survival analysis to compare time-to-event between groups.
“Most studies simply compare TV at a single day using t test, or use survival analysis to compare the time-to-event (i.e., time for TV to reach a threshold) between groups (4–6, 23).”
From Statistical Assessment of Drug Synergy from <i>In Vivo</i> Combination Studies Using Mouse Tumor Models (2023) · cites this paper as [6]
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- Authors
- O'Neil, J., Benita, Y., Feldman, I., Chenard, M., Roberts, B., Liu, Y., Li, J., Kral, A., Lejnine, S., Loboda, A., Arthur, W., Cristescu, R., Haines, B. B., Winter, C., Zhang, T., Bloecher, A., & Shumway, S. D.
- Affiliations
- 1Merck Research Laboratories, Boston, Massachusetts.
- Merck & Co., Inc., Rahway, NJ, USA (United States) (US)
- ORCID
- Venue
- Molecular Cancer Therapeutics
- Published
- 2016-06-01
- Volume
- 15
- Issue
- 6
- Pages
- 1155-1162
- ISSN
- 1535-7163 (ISSN-L)
- 1538-8514
- OpenAlex
- W2299417213
- Cited by
- 407
- References
- 3
- Citations by year
- 2026: 61 · 2025: 85 · 2024: 65 · 2023: 53 · 2022: 29 · 2021: 41 · 2020: 34 · 2019: 21 · 2018: 11 · 2017: 3 · 2016: 2
- FWCI
- 6.41
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Molecular Cancer Therapeutics (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › PI3K/AKT/mTOR signaling in cancer
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Health Sciences › Medicine › Pathology and Forensic Medicine › Cancer Mechanisms and Therapy
- Keywords
- combination therapy, synergistic drug combination, high-throughput compound screening, cancer cell lines, WEE1 inhibitor, AZD1775, ridaforolimus, mTOR inhibitors, anticancer drug discovery
- MeSH terms
- Animals, Antineoplastic Combined Chemotherapy Protocols, Cell Survival, Drug Screening Assays, Antitumor, Drug Synergism, Humans, Neoplasms, Experimental, Pyrazoles, Pyrimidines, Pyrimidinones, Random Allocation, Sirolimus, Xenograft Model Antitumor Assays, Cell Line, Tumor, Cell Proliferation, Mice, High-Throughput Screening Assays
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