ArticlePLoS computational biology2020
Multi-scale modeling of macrophage-T cell interactions within the tumor microenvironment.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
55 citing papers in PubMed, 89 citations in OpenAlex.
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- Coupled Cell-Intrinsic and Microenvironmental Heterogeneity Drives Divergent Trajectories in Castration-Resistant Prostate Cancer.bioRxiv : the preprint server for biology · 2026Article
- Multiscale predictive cellular modeling: integrating hypothesis grammars, digital twins, and multi-omics for In silico oncology and precision theranostics.Functional & integrative genomics · 2026Review
- Agent-based modeling demonstrates how target-independent processes supplement killing by antibody-drug conjugates in cancer therapy.PLoS computational biology · 2026Article
- Significance of monocyte-to-lymphocyte ratio as a prognostic factor in canine urothelial carcinoma: a retrospective study.The Journal of veterinary medical science · 2026Article
- Integrating single cell- and spatial- resolved transcriptomics unravels the inter-tumor heterogeneity and immunosuppressive landscape in HBV- and Clonorchis sinensis-associated hepatocellular carcinoma.Molecular cancer · 2026Article
- Identification and validation of prognostic genes related to glycolysis and M2 macrophage in hepatocellular carcinoma: an integrated analysis of bulk RNA sequencing and single-cell RNA sequencing.Frontiers in immunology · 2026Article
- A streamlined and comprehensive protocol for the generation and multi-omic analysis of human monocyte-derived macrophages.BMC biotechnology · 2025Article
- Advances in surrogate modeling for biological agent-based simulations: trends, challenges, and future prospects.Journal of mathematical biology · 2025Review
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- Multiscale mathematical model-informed reinforcement learning optimizes combination treatment scheduling in glioblastoma evolution.Science advances · 2025Article
- Biomimetic mineralized DCPA/ anti-CD47 containing thermo-sensitive injectable hydrogel for bone-metastatic prostate cancer treatment.Materials today. Bio · 2025Article
- Network analyses of brain tumor multiomic data reveal pharmacological opportunities to alter cell state transitions.NPJ systems biology and applications · 2025Article
- Mathematical models of intercellular signaling in breast cancer.Seminars in cancer biology · 2025Review
- Programmed Death Ligand-1 in Melanoma and Extracellular Vesicles Promotes Local and Regional Immune Suppression through M2-like Macrophage Polarization.The American journal of pathology · 2025Article
- Artificial intelligence and machine learning in the development of vaccines and immunotherapeutics-yesterday, today, and tomorrow.Frontiers in artificial intelligence · 2025Review
- A multiscale model of immune surveillance in micrometastases gives insights on cancer patient digital twins.NPJ systems biology and applications · 2024Article
- Spatial organization and stochastic fluctuations of immune cells impact clinical responsiveness to immunotherapy in melanoma patients.PNAS nexus · 2024Article
- Integrating mechanism-based T cell phenotypes into a model of tumor-immune cell interactions.APL bioengineering · 2024Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Within the tumor microenvironment, macrophages exist in an immunosuppressive state, preventing T cells from eliminating the tumor. Due to this, research is focusing on immunotherapies that specifically target macrophages in order to reduce their immunosuppressive capabilities and promote T cell function. In this study, we develop an agent-based model consisting of the interactions between macrophages, T cells, and tumor cells to determine how the immune response changes due to three macrophage-based immunotherapeutic strategies: macrophage depletion, recruitment inhibition, and macrophage reeducation. We find that reeducation, which converts the macrophages into an immune-promoting phenotype, is the most effective strategy and that the macrophage recruitment rate and tumor proliferation rate (tumor-specific properties) have large impacts on therapy efficacy. We also employ a novel method of using a neural network to reduce the computational complexity of an intracellular signaling mechanistic model.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.