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J Theor Biol. 2014 Jun 21;351:74-82. doi: 10.1016/j.jtbi.2014.02.028. Epub 2014 Mar 1.

A mathematical model for pancreatic cancer growth and treatments.

Author information

1
Department of Mathematics and Gonda brain research institute, Bar-Ilan University, Ramat-Gan 52900, Israel.
2
Department of Mathematics and Mathematical Biosciences Institute, Ohio State University, Columbus, OH 43210, United States. Electronic address: cxue@math.osu.edu.
3
Internal Medicine, Ohio State University, Columbus, OH 43210, United States.
4
Department of Mathematics and Mathematical Biosciences Institute, Ohio State University, Columbus, OH 43210, United States.

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.

KEYWORDS:

Immune response; Immunotherapy; Pancreatic cancer

PMID:
24594371
PMCID:
PMC4011486
DOI:
10.1016/j.jtbi.2014.02.028
[Indexed for MEDLINE]
Free PMC Article
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