Abstract 1132: A systems biology approach combining ProLiFiler and Cancer Data Miner for an enhanced preclinical characterization of the WEE-1 inhibitor Adavosertib

Abstract Adavosertib (AZD1775, MK-1775), a clinical stage inhibitor of the tyrosine kinase WEE1, was investigated in a cell proliferation and survival assay with 140 human cancer cell lines (CLs) representing all major tumor types (ProLiFiler platform of Reaction Biology) followed by mechanism of action (MoA) and biomarker analyses using 4HF Biotec’s Cancer Data Miner in silico platform. Adavosertib exhibited a broad anti-cancer activity across all hematological and solid tumor types with IC50 values ranging from 0.06 to 10 µM (median: 0.38 µM), matching the consistently high expression of the WEE1 gene. Among 900 reference compounds, the activity profile of adavosertib correlated best with the profiles of compounds targeting the replication stress response including other WEE1 inhibitors but also inhibitors of checkpoint kinase 1 and 2 (CHK1/2) or ataxia telangiectasia-mutated (ATM). Significant correlations were also seen with compounds blocking mitosis, DNA replication and DNA repair. Interestingly, we observed a subset of cell lines that were resistant to both DNA synthesis and PARP inhibitors but were sensitive to WEE1 inhibition. Moreover, by using multiple datasets of WEE1 inhibitors connected to the molecular annotations of CLs for a data driven biomarker screening, we identified MYC mutations as a predictive marker of sensitivity and PIK3CA or ERBB2 gene amplifications as predictors of resistance. Transcriptome analysis identified up to 900 genes for which higher expression in CLs was associated with CL sensitivity to the compound. Preliminary pathway analysis indicated that these genes are well represented among nuclear factor and Myc-regulated genes. In conclusion, our studies demonstrate broad anticancer activity of adavosertib and confirm its proposed MoA. The biomarkers we identified will facilitate the selection of pre-clinical in vivo tumor models and, if confirmed, even patient selection for clinical trials. The combined use of the ProLiFiler and Cancer Data Miner Platforms has the potential to accelerate and de-risk the development of anti-cancer agents. Citation Format: Vincent Vuaroqueaux, Daniel Feger, Anne-Lise Peille, Oliver Siedentopf, Sadhana Panzade, Sarah Ulrich, Sebastian Dempe, Heinz-Herbert Fiebig, Jan Erik Ehlert. A systems biology approach combining ProLiFiler and Cancer Data Miner for an enhanced preclinical characterization of the WEE-1 inhibitor Adavosertib [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1132.