Abstract 667: Identification of biomarkers of response to MDM2 inhibition in solid tumours using computational, multi-omics approaches

Abstract Background High-throughput drug screening and computational methods to associate genomic features of cell lines to drug sensitivity are valuable tools for predicting biomarkers of sensitivity. In addition, integrating genomic features to expression-based patterns could improve biomarker prediction and patient stratification. Particularly weighted gene co-expression networks represent an effective approach to identify key modules and possible biological mechanisms of sensitivity. Using a combination of cell panel screening and gene co-expression networks, we predicted markers of sensitivity to ASTX295 (MDM2i) in cancer cell lines and confirmed expression-based signatures in publicly available clinical datasets. Method ASTX295 was screened in a panel of 210 p53 wild-type cancer cell lines derived from a range of tumor tissues. ANOVA was used to identify significant associations of genomics features of cell lines to drug response. Transcriptomics profiling of apoptotic and non-apoptotic patient-derived cell lines was performed and significant differentially expressed genes were identified. Further, pathway enrichment and expression-based signatures identified in cell lines were further confirmed in TCGA patient data using weighted gene co-expression network analysis (WGCNA). Expression modules identified by WGCNA were correlated to genomic features and clinical parameters to identify potentially clinically relevant biomarkers. Results Analysis of the cell panel data identified CDKN2A loss as a statistically significant biomarker predictive of sensitivity to ASTX295. As mesothelioma is one of the indications with high prevalence of loss of CDKN2A, the anti-proliferative activity of ASTX295 was further confirmed in an independent panel of p53 wild-type, patient-derived mesothelioma cell lines. Further, pathway and transcriptional regulator analysis identified the Interferon signalling as significantly enriched in apoptotic cell lines and was confirmed in a TCGA mesothelioma patient data set and the module was found to be significantly correlated with a subgroup of P53 wild-type patients with CDKN2A loss. In conclusion, combining cell panel drug screening with co-expression networks helped to identify biomarkers associated with ASTX295 sensitivity, and provided new insights into the underlying mechanism of ASTX295 response. Citation Format: Harpreet Kaur Saini, Maria Ahn, George Ward, Justyna Kucia-Tran, Christina Gewinner, Nicola Ferrari, Jessica Brothwood, Luke Bevan, Matthew Davis, Lynsey Fazal, Martin Sims, Marc O'Reilly, Gianni Chessari, Roberta Ferraldeschi, John Lyons, Nicola Wallis, Neil Thompson. Identification of biomarkers of response to MDM2 inhibition in solid tumours using computational, multi-omics approaches abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 667.