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Updated: Jul 17, 2025
A Three-Dimensional Spheroid Model to Investigate the Tumor-Stromal Interaction in Hepatocellular Carcinoma
Published on: September 30, 2021
Informing virtual clinical trials of hepatocellular carcinoma with spatial multi-omics analysis of a human
Shuming Zhang1, Atul Deshpande2,3,4, Babita K Verma1
1Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Abstract:
Human clinical trials are important tools to advance novel systemic therapies improve treatment outcomes for cancer patients. The few durable treatment options have led to a critical need to advance new therapeutics in hepatocellular carcinoma (HCC). Recent human clinical trials have shown that new combination immunotherapeutic regimens provide unprecedented clinical response in a subset of patients. Computational methods that can simulate tumors from mathematical equations describing cellular and molecular interactions are emerging as promising tools to simulate the impact of therapy entirely in silico. To facilitate designing dosing regimen and identifying potential biomarkers, we developed a new computational model to track tumor progression at organ scale while reflecting the spatial heterogeneity in the tumor at tissue scale in HCC. This computational model is called a spatial quantitative systems pharmacology (spQSP) platform and it is also designed to simulate the effects of combination immunotherapy. We then validate the results from the spQSP system by leveraging real-world spatial multi-omics data from a neoadjuvant HCC clinical trial combining anti-PD-1 immunotherapy and a multitargeted tyrosine kinase inhibitor (TKI) cabozantinib. The model output is compared with spatial data from Imaging Mass Cytometry (IMC). Both IMC data and simulation results suggest closer proximity between CD8 T cell and macrophages among non-responders while the reverse trend was observed for responders. The analyses also imply wider dispersion of immune cells and less scattered cancer cells in responders' samples. We also compared the model output with Visium spatial transcriptomics analyses of samples from post-treatment tumor resections in the original clinical trial. Both spatial transcriptomic data and simulation results identify the role of spatial patterns of tumor vasculature and TGFβ in tumor and immune cell interactions. To our knowledge, this is the first spatial tumor model for virtual clinical trials at a molecular scale that is grounded in high-throughput spatial multi-omics data from a human clinical trial.
Insights
A new spatial quantitative systems pharmacology (spQSP) model simulates hepatocellular carcinoma (HCC) tumor progression and immunotherapy response. Validated with clinical trial data, it reveals spatial immune cell interactions linked to treatment outcomes, aiding biomarker discovery.
Area of Science:
- Computational biology and bioinformatics
- Cancer research and immunology
- Pharmacology and drug development
Background:
- Hepatocellular carcinoma (HCC) treatment options are limited, necessitating novel therapeutic strategies.
- Combination immunotherapies show promise but require better predictive models for patient selection and regimen design.
- Existing computational models often lack the spatial resolution to capture tumor heterogeneity and immune interactions.
Approach:
- Developed a novel spatial quantitative systems pharmacology (spQSP) platform to simulate HCC tumor progression at organ and tissue scales.
- Integrated mathematical modeling with spatial multi-omics data from a human clinical trial of anti-PD-1 immunotherapy and cabozantinib.
- Validated model predictions against Imaging Mass Cytometry (IMC) and Visium spatial transcriptomics data from HCC patient samples.
Key Points:
- The spQSP model accurately reflects spatial heterogeneity and predicts treatment response based on immune cell proximity and distribution.
- Simulation and clinical data indicate distinct spatial patterns of CD8 T cells and macrophages in responders versus non-responders.
- Model and data analyses highlight the role of tumor vasculature and TGFβ in mediating immune cell interactions within the tumor microenvironment.
Conclusions:
- This study presents the first spatial tumor model for virtual clinical trials at a molecular scale, grounded in high-throughput spatial multi-omics data.
- The spQSP platform facilitates the design of optimal dosing regimens and identifies potential biomarkers for combination immunotherapies in HCC.
- The findings advance our understanding of spatial immune dynamics in HCC and offer a powerful tool for preclinical and clinical research.
