ArticleBulletin of mathematical biology2017
Modeling the Dichotomy of the Immune Response to Cancer: Cytotoxic Effects and Tumor-Promoting Inflammation.
Article in Bulletin of mathematical biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 2 citations in OpenAlex.
- A multiscale model reveals how ERK/p38-regulated dormancy shapes tumor-immune dynamics and immunoediting outcomes.Frontiers in immunology · 2026Article
- Digital Twin Meets the Bench: Natural Compounds Reshape the Ovarian Cancer Microenvironment.Biomedicines · 2025Article
- Targeting inflammation in cancer therapy: from mechanistic insights to emerging therapeutic approaches.Journal of translational medicine · 2025Review
- The role of depression in the progression of tumor cell inflammation and the potential regulatory mechanisms of aerobic exercise: a narrative review from molecular and cellular perspectives.Frontiers in psychiatry · 2025Review
- Practical parameter identifiability and handling of censored data with Bayesian inference in mathematical tumour models.NPJ systems biology and applications · 2024Article
- Mitigating non-genetic resistance to checkpoint inhibition based on multiple states of immune exhaustion.NPJ systems biology and applications · 2024Article
- Optimal dosage protocols for mathematical models of synergy of chemo- and immunotherapy.Frontiers in immunology · 2023Article
- A practical guide for the generation of model-based virtual clinical trials.Frontiers in systems biology · 2023Article
- Modeling cancer immunoediting in tumor microenvironment with system characterization through the ising-model Hamiltonian.BMC bioinformatics · 2022Article
- Analysis of the Equilibrium Phase in Immune-Controlled Tumors Provides Hints for Designing Better Strategies for Cancer Treatment.Frontiers in oncology · 2022Article
- Forecasting Individual Patient Response to Radiation Therapy in Head and Neck Cancer With a Dynamic Carrying Capacity Model.International journal of radiation oncology, biology, physics · 2021Article
- Potential of Immunotherapies in Treating Hematological Cancer-Infection Comorbidities-A Mathematical Modelling Approach.Cancers · 2021Article
- Data-Driven Mathematical Model of Osteosarcoma.Cancers · 2021Article
- Predator-Prey in Tumor-Immune Interactions: A Wrong Model or Just an Incomplete One?Frontiers in immunology · 2021Article
- Implications of immune-mediated metastatic growth on metastatic dormancy, blow-up, early detection, and treatment.Journal of mathematical biology · 2020Article
- The Goldilocks Window of Personalized Chemotherapy: Getting the Immune Response Just Right.Cancer research · 2019Article
- Mathematical modeling of tumor-immune cell interactions.Journal of theoretical biology · 2019Review
- How Should Cancer Models Be Constructed?Cancer control : journal of the Moffitt Cancer CenterReview
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
Abstract
Although the immune response is often regarded as acting to suppress tumor growth, it is now clear that it can be both stimulatory and inhibitory. The interplay between these competing influences has complex implications for tumor development, cancer dormancy, and immunotherapies. In fact, early immunotherapy failures were partly due to a lack in understanding of the nonlinear growth dynamics these competing immune actions may cause. To study this biological phenomenon theoretically, we construct a minimally parameterized framework that incorporates all aspects of the immune response. We combine the effects of all immune cell types, general principles of self-limited logistic growth, and the physical process of inflammation into one quantitative setting. Simulations suggest that while there are pro-tumor or antitumor immunogenic responses characterized by larger or smaller final tumor volumes, respectively, each response involves an initial period where tumor growth is stimulated beyond that of growth without an immune response. The mathematical description is non-identifiable which allows an ensemble of parameter sets to capture inherent biological variability in tumor growth that can significantly alter tumor-immune dynamics and thus treatment success rates. The ability of this model to predict non-intuitive yet clinically observed patterns of immunomodulated tumor growth suggests that it may provide a means to help classify patient response dynamics to aid identification of appropriate treatments exploiting immune response to improve tumor suppression, including the potential attainment of an immune-induced dormant state.
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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.