A pan-cancer screen identifies drug combination benefit in cancer cell lines at the individual and population level
Combining drugs can enhance their clinical efficacy, but the number of possible combinations and inter-tumor heterogeneity make identifying effective combinations challenging, while existing approaches often overlook clinically relevant activity. We screen one of the largest cell line panels (N = 757) with 51 clinically relevant combinations and identify responses at the level of individual cell lines and tissue populations. We establish three response classes to model cellular effects beyond monotherapy: synergy, Bliss additivity, and independent drug action (IDA). Synergy is rare (11% of responses) and frequently efficacious (>50% viability reduction), whereas Bliss and IDA are more frequent but less frequently efficacious. We introduce "efficacious combination benefit" (ECB) to describe high-efficacy responses classified as either synergy, Bliss, or IDA. We identify ECB biomarkers in vitro and show that ECB predicts response in patient-derived xenografts better than synergy alone. Our work here provides a valuable resource and framework for preclinical evaluation and the development of combination treatments.
Authors
- Syd Barthorpe
- Lodewyk F.A. Wessels (ORCID: https://orcid.org/0000-0002-1656-6995)
- Charlotte Tolley (ORCID: https://orcid.org/0000-0002-1119-7983)
- Elizabeth A. Coker (ORCID: https://orcid.org/0000-0003-4934-8887)
- Alexandra Beck (ORCID: https://orcid.org/0009-0001-0244-5711)
- Laura Richardson (ORCID: https://orcid.org/0000-0002-8075-3816)
- Patricia Jaaks (ORCID: https://orcid.org/0000-0002-0041-4313)
- Caitlin Hall (ORCID: https://orcid.org/0000-0002-5713-5980)
- Howard Lightfoot (ORCID: https://orcid.org/0000-0003-2082-9986)
- Tatiana Mironenko
- Nanne Aben
- Ermira Lleshi
- Daniël J. Vis (ORCID: https://orcid.org/0009-0003-9522-5535)
- James Hall (ORCID: https://orcid.org/0000-0002-8124-5434)
- Mathew J. Garnett
Institutions
- Wellcome Sanger Institute (GB)
- The Netherlands Cancer Institute (NL)
- Oncode Institute (NL)
- Delft University of Technology (NL)
Publication Details
- Journal
- Cell Reports Medicine
- Published
- 2024-08-01
- DOI
- https://doi.org/10.1016/j.xcrm.2024.101687
- Citations
- 8
- Primary Topic
- Cell Image Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 5.30