Gustavo Guerrero1, Piergiorgio Pettazzoni1, Dominik Heer1, Helene Meistermann1, Christophe Meille1, Jasmin Emmenegger1, Sophia M. Blake2, Neil Parrott1, Cristina Santini1, Antoine Soubret1, Stephen Fowler1
1Roche Pharma Research and Early Development, Roche Innovation Center, 2Roche Pharma Research and Early Development, Roche Innovation Center
Introduction/Objectives: Werner (WRN) helicase is a synthetic lethal target in microsatellite instable (MSI) cancer cells. WRN helicase depletion induces apoptosis and cell cycle arrest in MSI cells [1,2], highlighting its potential as a therapeutic target for MSI tumors. RO7589831 is a novel irreversible WRN helicase inhibitor that demonstrates selective antitumor activity in MSI cell lines by triggering G2/M phase accumulation followed by apoptosis [2]. However, the kinetics of response across diverse MSI cell lines, and the dynamics between WRN target engagement and cell growth inhibition are only partially understood. An in silico model-based approach is used to understand the kinetics of WRN helicase inhibition and its effects on cell cycle and cell growth inhibition, enhancing knowledge of RO7589831’s mode of action. Methods: We developed a comprehensive modeling framework that integrates a covalent WRN Target Engagement (TE) model with a mechanistic cell cycle model. For the TE model, a covalent inhibition model was implemented [3] to simulate the inactivation of WRN helicase by RO7589831. This model was calibrated with in vitro binding data of RO7589831 to WRN helicase in HCT116 MSI cell lines with various RO7589831 concentrations and washout periods. The mechanistic cell cycle model was developed comprising four compartments that represent the phases of the cell cycle: G1, S, G2/M, and a G2 damage (G2D) compartment [4]. This model simulates cell accumulation in the G2 phase as observed in preclinical data. Cells in the G2D compartment can undergo apoptosis or be repaired. Integration between the two models was achieved by modulating the transition from the S phase to the G2D compartment by the amount of free WRN helicase from the TE model. The integrated model was calibrated using HCT116 derived in vitro cell viability and cell cycle data, at different RO7589831 dosing and washout times. Results: The WRN TE model captured WRN kinetics in the presence of different concentrations of RO7589831, achieving a relative root mean square error (rRMSE) of 9.05% between simulated and experimental data. The model reproduced the rapid dynamics of WRN helicase inhibition and the recovery of WRN helicase levels following the removal of RO7589831. The integrated mechanistic cell cycle model accurately describes cell growth inhibition in HCT116 cells for RO7589831 concentrations from 1 nM to 10,000 nM, with washout periods from 2 to 48 hours, achieving a rRMSE of 7.49%. These results highlight the mechanistic model’s capability to reproduce cell growth inhibition for various concentrations of RO7589831, driven by target engagement dynamics and their effects on the cell cycle. Conclusions: This study presents a comprehensive mechanistic model that integrates WRN target engagement with cell cycle dynamics to quantitatively describe the action of RO7589831 in MSI HCT116 cells. The framework not only reproduces the experimental data with high accuracy but also provides a valuable tool for exploring variability in cell growth inhibition across different MSI cell lines. Moreover, the model supports hypothesis generation for combination treatments with cell cycle–targeted agents and offers a foundation for future in vivo efficacy predictions.
1. Baltgalvis, K. A., et al. (2024). Chemoproteomic discovery of a covalent allosteric inhibitor of WRN helicase. Nature, 629(8011) 2. Morales-Juarez, D. A., et al. (2022). Clinical prospects of WRN inhibition as a treatment for MSI tumours. npj Precision Oncology 3. Strelow, J. M. (2017). A Perspective on the Kinetics of Covalent and Irreversible Inhibition. SLAS Discovery: Advancing Life Sciences R & D 4. Checkley, S., et al. (2015). Bridging the gap between in vitro and in vivo: Dose and schedule predictions for the ATR inhibitor AZD6738. Scientific Reports
Reference: PAGE 33 (2025) Abstr 11458 [www.page-meeting.org/?abstract=11458]
Poster: Drug/Disease Modelling - Oncology