Abstract SY14-02: Mapping synthetic lethal interactions at scale: A functional genomics approach to cancer therapeutic discovery
Abstract The Cancer Dependency Map (DepMap) is an ongoing initiative to identify and explore synthetic lethal targets, by systematically linking tumor molecular alterations to gene dependencies and drug sensitivities. The resource used by scientists worldwide has significantly contributed to both basic and translational cancer research and has provided the community with a landscape view of synthetic lethal targets. Numerous targets identified through DepMap are actively under investigation, with several already advancing into clinical trials, highlighting their clinical relevance and potential. For instance, we recently discovered a synthetic lethal interaction involving the PELO-HBS1L and SKI complex, both involved in mRNA quality control. PELO is a promising synthetic lethal target in cancers with SKI complex deficiencies, such as those with FOCAD deletions or high microsatellite instability. Despite the progress, much work remains to fully exploit cancer dependencies. We have integrated next-generation patient-derived models, including organoids and neurospheres grown in 3D to better represent various cancer subtypes. Additionally, we used di-genic screening libraries to uncover synthetic lethal dependencies previously masked due to paralog redundancy. We are also actively expanding multi-omics datasets and building computational features that will enable the identification of novel molecular links to synthetic lethal dependencies. DepMap continues to grow with the ultimate goal of creating a comprehensive and detailed landscape of cancer vulnerabilities to accelerate precision cancer medicine. Citation Format: Francisca Vazquez. Mapping synthetic lethal interactions at scale: A functional genomics approach to cancer therapeutic discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr SY14-02.
Authors
- Francisca Vázquez (ORCID: https://orcid.org/0000-0002-2857-4685)
Institutions
- Broad Institute (US)
Publication Details
- Journal
- Cancer Research
- Published
- 2025-04-25
- DOI
- https://doi.org/10.1158/1538-7445.am2025-sy14-02
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00