ArticleJournal of theoretical biology2014
A mathematical model for pancreatic cancer growth and treatments.
Article in Journal of theoretical biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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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
26 citing papers in PubMed.
- Tracking inflammation status for improving patient prognosis: A review of current methods, unmet clinical needs and opportunities.Biotechnology advances · 2025Review
- Spatio-Temporal Dynamics of MBulletin of mathematical biology · 2025Article
- Oxygen, angiogenesis, cancer and immune interplay in breast tumour microenvironment: a computational investigation.Royal Society open science · 2024Article
- Predicting lung cancer's metastats' locations using bioclinical model.Frontiers in medicine · 2024Article
- Examining the efficacy of localised gemcitabine therapy for the treatment of pancreatic cancer using a hybrid agent-based model.PLoS computational biology · 2023Article
- Systems biology of autophagy in leishmanial infection and its diverse role in precision medicine.Frontiers in molecular biosciences · 2023Review
- The impact of tumor associated macrophages on tumor biology under the lens of mathematical modelling: A review.Frontiers in immunology · 2022Review
- Prediction of anti-CD25 and 5-FU treatments efficacy for pancreatic cancer using a mathematical model.BMC cancer · 2021Article
- Mathematical modeling of ventilator-induced lung inflammation.Journal of theoretical biology · 2021Article
- Modeling the effects of EMT-immune dynamics on carcinoma disease progression.Communications biology · 2021Article
- Quantitative Systems Pharmacology Approaches for Immuno-Oncology: Adding Virtual Patients to the Development Paradigm.Clinical pharmacology and therapeutics · 2021Review
- Computational modeling of therapy on pancreatic cancer in its early stages.Biomechanics and modeling in mechanobiology · 2020Article
- Mathematical Modeling to Address Challenges in Pancreatic Cancer.Current topics in medicinal chemistry · 2020Article
- Modeling of Nanotherapy Response as a Function of the Tumor Microenvironment: Focus on Liver Metastasis.Frontiers in bioengineering and biotechnology · 2020Review
- Investigating Macrophages Plasticity Following Tumour-Immune Interactions During Oncolytic Therapies.Acta biotheoretica · 2019Article
- Quantifying Cancer Epithelial-Mesenchymal Plasticity and its Association with Stemness and Immune Response.Journal of clinical medicine · 2019Review
- Instantaneous mutation rate in cancer initiation and progression.BMC systems biology · 2018Article
- Review
- Modeling the Dichotomy of the Immune Response to Cancer: Cytotoxic Effects and Tumor-Promoting Inflammation.Bulletin of mathematical biology · 2017Article
- Dynamic interplay between tumour, stroma and immune system can drive or prevent tumour progression.Convergent science physical oncology · 2017Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Pancreatic cancer is one of the most deadly types of cancer and has extremely poor prognosis. This malignancy typically induces only limited cellular immune responses, the magnitude of which can increase with the number of encountered cancer cells. On the other hand, pancreatic cancer is highly effective at evading immune responses by inducing polarization of pro-inflammatory M1 macrophages into anti-inflammatory M2 macrophages, and promoting expansion of myeloid derived suppressor cells, which block the killing of cancer cells by cytotoxic T cells. These factors allow immune evasion to predominate, promoting metastasis and poor responsiveness to chemotherapies and immunotherapies. In this paper we develop a mathematical model of pancreatic cancer, and use it to qualitatively explain a variety of biomedical and clinical data. The model shows that drugs aimed at suppressing cancer growth are effective only if the immune induced cancer cell death lies within a specific range, that is, the immune system has a specific window of opportunity to effectively suppress cancer under treatment. The model results suggest that tumor growth rate is affected by complex feedback loops between the tumor cells, endothelial cells and the immune response. The relative strength of the different loops determines the cancer growth rate and its response to immunotherapy. The model could serve as a starting point to identify optimal nodes for intervention against pancreatic cancer.
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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.