ArticlePLoS computational biology2022
Simulations of tumor growth and response to immunotherapy by coupling a spatial agent-based model with a whole-patient quantitative systems pharmacology model.
Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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Who cites it
45 citing papers in PubMed.
- Virtual clinical trials of anti-PD-1 and anti-CTLA-4 immunotherapy in advanced hepatocellular carcinoma using a quantitative systems pharmacology model.Journal for immunotherapy of cancer · 2022Trial
- A Comparison of Mechanisms Driving Lesion Outcomes During Lung Tumor and Tuberculosis Granuloma Formation.Bulletin of mathematical biology · 2026Article
- Bridging BET bromodomain and immune checkpoint inhibitors through generative bioorganic frameworks for next-generation cancer immunotherapy.RSC medicinal chemistry · 2026Review
- Agent-Based Simulations of Lung Tumor Evolution Suggest That Ongoing Cell Competition Drives Realistic Clonal Expansions.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- OPTIMIS: Optimizing Personalized Therapies through Integrated Multiscale Intelligent Simulation.bioRxiv : the preprint server for biology · 2026Article
- A review on in-silico analysis of immune cell trafficking and interactions with the tumour microenvironment.Frontiers in oncology · 2026Review
- Harnessing Next-Generation 3D Cancer Models to Elucidate Tumor-Microbiome Crosstalk.Advanced healthcare materials · 2026Review
- A Roadmap for the Future of Systems Biology in Cancer Research.Cancer research · 2025Review
- Probabilistic modeling of cell cycle dynamics in response to cell cycle targeting chemotherapy drugs to guide treatment strategies.PLoS computational biology · 2025Article
- A Systematic Comparative Analysis of Tumor Size Models Based on Erlotinib Clinical Data in Advanced NSCLC.CPT: pharmacometrics & systems pharmacology · 2025Article
- Quantitative Calibration of a Spatial QSP Model Identifies Fibroblast Impact on HCC Immunotherapy.bioRxiv : the preprint server for biology · 2025Article
- Article
- Systems biology successes and areas for opportunity in prostate cancer.Endocrine-related cancer · 2025Review
- Mechanistic insight for T-cell exclusion by cancer-associated fibroblasts in human lung cancer.eLife · 2025Article
- A Multiple-Model-Informed Drug-Development Approach for Optimal Regimen Selection of an Oncolytic Virus in Combination With Pembrolizumab.CPT: pharmacometrics & systems pharmacology · 2025Article
- Spatial Architecture of Single-Cell and Vasculature in Tumor Microenvironment Predicts Clinical Outcomes in Triple-Negative Breast Cancer.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2025Article
- Integrative multi-omics stratification and translational evaluation of Treg-targeted combination immunotherapy in breast cancer.Frontiers in oncology · 2025Article
- Future Directions for Quantitative Systems Pharmacology.Handbook of experimental pharmacology · 2025Review
- Quantitative Systems Pharmacology Modeling in Immuno-Oncology: Hypothesis Testing, Dose Optimization, and Efficacy Prediction.Handbook of experimental pharmacology · 2025Review
- Agent-based modeling in cancer biomedicine: applications and tools for calibration and validation.Cancer biology & therapy · 2024Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Quantitative systems pharmacology (QSP) models and spatial agent-based models (ABM) are powerful and efficient approaches for the analysis of biological systems and for clinical applications. Although QSP models are becoming essential in discovering predictive biomarkers and developing combination therapies through in silico virtual trials, they are inadequate to capture the spatial heterogeneity and randomness that characterize complex biological systems, and specifically the tumor microenvironment. Here, we extend our recently developed spatial QSP (spQSP) model to analyze tumor growth dynamics and its response to immunotherapy at different spatio-temporal scales. In the model, the tumor spatial dynamics is governed by the ABM, coupled to the QSP model, which includes the following compartments: central (blood system), tumor, tumor-draining lymph node, and peripheral (the rest of the organs and tissues). A dynamic recruitment of T cells and myeloid-derived suppressor cells (MDSC) from the QSP central compartment has been implemented as a function of the spatial distribution of cancer cells. The proposed QSP-ABM coupling methodology enables the spQSP model to perform as a coarse-grained model at the whole-tumor scale and as an agent-based model at the regions of interest (ROIs) scale. Thus, we exploit the spQSP model potential to characterize tumor growth, identify T cell hotspots, and perform qualitative and quantitative descriptions of cell density profiles at the invasive front of the tumor. Additionally, we analyze the effects of immunotherapy at both whole-tumor and ROI scales under different tumor growth and immune response conditions. A digital pathology computational analysis of triple-negative breast cancer specimens is used as a guide for modeling the immuno-architecture of the invasive front.
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