Abstract IA04: Using GENIE data to drive oncology target identification and drug development

Abstract Of oncology drugs entering clinical development, only around 5% reach full approval, with most novel agents failing due to lack of efficacy. Importantly, the chances of success improve significantly when a precision approach is used, especially when new drugs target specific genomic alterations present in cancer cells. The availability of high quality, well curated genomic data from large and relevant patient populations is key to driving precision oncology. This talk will outline two use cases where AACR Project GENIE data has been successfully used in the drug development process. In the first use case, analysis of GENIE data is used to parse somatic mutations in cancer associated genes, to distinguish biological driver mutations from passenger events and thus identify patients who may benefit from molecularly targeted therapy. Clinical reporting of tumour comprehensive genomic profiling can be time consuming and cumbersome, with currently available clinical guidelines often mandating manual interrogation of individual mutations using processes that are not scalable for routine clinical practice. By leveraging cancer as a process of positive selection of biologically relevant mutations, the use of large datasets such as GENIE provides a rapid, scalable and biologically sound approach to somatic variant annotation. In the second use case, analysis of GENIE data was used to identify a potential biomarker for a novel approach to the treatment of cancer. Dencatistat is a first in class inhibitor of the enzyme CTP synthase 1 (CTPS1). Lymphoid cells are dependent on CTPS1 for the synthesis of CTP for DNA replication, whereas epithelial tissues can potentially utilise the isoenzyme CTPS2 (which is not inhibited by dencatistat). GENIE copy number data were interrogated for somatic alterations of CTPS1 or CTPS2 as potential biomarkers of response; deletion of CTPS2 was identified in a proportion of samples with the highest prevalence found in ovarian cancer, subsequently confirmed in independent datasets. Preclinical studies, including siRNA, CRISPR gene knock out and patient derived xenografts, support the hypothesis that loss of CTPS2 results in synthetic lethal dependence on CTPS1. The on-going IMAGINE clinical trial (ISRCTN42303887) offers comprehensive genomic profiling to individuals living with cancer who have exhausted standard of care therapy, with variant annotation powered by GENIE data. Dencatistat, an orally available and highly potent inhibitor of CTPS1, is currently in clinical development for the treatment of lymphoma (NCT05463263); in a second study, dose escalation in solid tumours will be followed by safety expansion cohorts for patients with CTPS2 null cancers (NCT06297525). Together, these two use cases exemplify how high quality, clinically relevant genomic datasets can be used to accelerate drug development. Citation Format: Philip A. Beer, Paul Grimwood, Andrew E. Parker, Patricia Roxburgh. Using GENIE data to drive oncology target identification and drug development [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2025 Oct 22-26; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2025;24(10 Suppl):Abstract nr IA04.