ArticleJournal for immunotherapy of cancer2018
Mathematical modeling of tumor-associated macrophage interactions with the cancer microenvironment.
Article in Journal for immunotherapy of cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.
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Who cites it
59 citing papers in PubMed, 107 citations in OpenAlex.
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- Role of intratumoral heterogeneity in metastatic progression and drug resistance.Discover oncology · 2025Review
- Optimizing therapeutic outcomes with Mechanotherapy and Ultrasound Sonopermeation in solid tumors.PLoS computational biology · 2025Article
- Mathematical model of tumor-macrophage dynamics in glioma to advance myeloid-targeted therapies.Computers in biology and medicine · 2025Article
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- Mathematical model of tumor-macrophage dynamics in glioma to advance myeloid-targeted therapies.bioRxiv : the preprint server for biology · 2025Article
- Spatio-Temporal Dynamics of MBulletin of mathematical biology · 2025Article
- Mathematical models of intercellular signaling in breast cancer.Seminars in cancer biology · 2025Review
- Synergistic mechanotherapy and sonopermeation guided by mathematical modeling for solid tumor treatment.Frontiers in drug delivery · 2025Article
- Osteosarcoma immune microenvironment: cellular struggle and novel therapeutic insights.Frontiers in immunology · 2025Review
- Oxygen, angiogenesis, cancer and immune interplay in breast tumour microenvironment: a computational investigation.Royal Society open science · 2024Article
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- Integrating mechanism-based T cell phenotypes into a model of tumor-immune cell interactions.APL bioengineering · 2024Article
- Glutamine metabolic microenvironment drives M2 macrophage polarization to mediate trastuzumab resistance in HER2-positive gastric cancer.Cancer communications (London, England) · 2023Article
- Calibrating agent-based models to tumor images using representation learning.PLoS computational biology · 2023Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundImmuno-oncotherapy has emerged as a promising means to target cancer. In particular, therapeutic manipulation of tumor-associated macrophages holds promise due to their various and sometimes opposing roles in tumor progression. It is established that M1-type macrophages suppress tumor progression while M2-types support it. Recently, Tie2-expressing macrophages (TEM) have been identified as a distinct sub-population influencing tumor angiogenesis and vascular remodeling as well as monocyte differentiation.
methodsThis study develops a modeling framework to evaluate macrophage interactions with the tumor microenvironment, enabling assessment of how these interactions may affect tumor progression. M1, M2, and Tie2 expressing variants are integrated into a model of tumor growth representing a metastatic lesion in a highly vascularized organ, such as the liver. Behaviors simulated include M1 release of nitric oxide (NO), M2 release of growth-promoting factors, and TEM facilitation of angiogenesis via Angiopoietin-2 and promotion of monocyte differentiation into M2 via IL-10.
resultsThe results show that M2 presence leads to larger tumor growth regardless of TEM effects, implying that immunotherapeutic strategies that lead to TEM ablation may fail to restrain growth when the M2 represents a sizeable population. As TEM pro-tumor effects are less pronounced and on a longer time scale than M1-driven tumor inhibition, a more nuanced approach to influence monocyte differentiation taking into account the tumor state (e.g., under chemotherapy) may be desirable.
conclusionsThe results highlight the dynamic interaction of macrophages within a growing tumor, and, further, establish the initial feasibility of a mathematical framework that could longer term help to optimize cancer immunotherapy.
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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.