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Quantitative systems pharmacology modeling of tumor heterogeneity in response to BH3-mimetics using virtual tumors
Thibaud Derippe1,2,3, Sylvain Fouliard1, Xavier Decleves2
1Institut de Recherches Internationales Servier, Suresnes, France.
Abstract:
Both primary and acquired resistance mechanisms that involve intra-tumoral cell heterogeneity limit the use of BH3-mimetics to trigger tumor cell apoptosis. This article proposes a new quantitative systems pharmacology (QSP)-based methodology in which cell viability assays are used to calibrate virtual tumors (VTs) made of virtual cells whose fate is determined by simulations from an apoptosis QSP model. VTs representing SU-DHL-4 and KARPAS-422 cell lines were calibrated using in vitro data involving venetoclax (anti-BCL2), A-1155463 (anti-BCLXL), and/or A-1210477 (anti-MCL1). The calibrated VTs provide insights into the combination of several BH3-mimetics, such as the distinction between cells eliminated by at least one of the drugs (monotherapies) from the cells eliminated by a pharmacological combination only. Calibrated VTs can also be used as initial conditions in an agent-based model (ABM) framework, and a minimal ABM was developed to bridge in vitro SU-DHL-4 cell viability results to tumor growth inhibition experiments in mice.
Insights
This study introduces a new quantitative systems pharmacology (QSP) method to create virtual tumors. This approach models drug resistance and predicts the effectiveness of BH3-mimetic combinations for cancer therapy.
Area of Science:
- Pharmacology
- Computational Biology
- Oncology
Background:
- Intra-tumoral cell heterogeneity drives resistance to BH3-mimetic drugs, limiting their therapeutic efficacy.
- Understanding resistance mechanisms is crucial for developing effective combination therapies against cancer.
Purpose of the Study:
- To develop a quantitative systems pharmacology (QSP) methodology for calibrating virtual tumors (VTs).
- To simulate the effects of BH3-mimetic drugs and their combinations on cancer cell apoptosis.
- To bridge in vitro findings to in vivo tumor growth inhibition using an agent-based model (ABM).
Main Methods:
- Calibrated virtual tumors (VTs) using in vitro cell viability data for SU-DHL-4 and KARPAS-422 cell lines.
- Simulated apoptosis pathways using a QSP model with BH3-mimetics targeting BCL2, BCL-XL, and MCL1.
- Integrated calibrated VTs into a minimal agent-based model (ABM) to predict tumor growth inhibition.
Main Results:
- The calibrated VTs accurately represented cell line responses to monotherapy and combination treatments with BH3-mimetics.
- Distinguished cell populations sensitive to monotherapy versus combination therapy.
- Successfully bridged in vitro cell viability to in vivo tumor growth inhibition in a mouse model.
Conclusions:
- The proposed QSP-based VT methodology offers a powerful tool for predicting BH3-mimetic combination efficacy.
- This approach can elucidate complex drug resistance mechanisms driven by cell heterogeneity.
- The integration with ABM provides a framework for translating in vitro predictions to in vivo outcomes in cancer treatment.
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