title: A mathematical model for pancreatic cancer growth and treatments.
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.
authors.affiliation: Department of Mathematics and Gonda brain research institute, Bar-Ilan University, Ramat-Gan 52900, Israel.
authors.forename: Yoram
authors.initials: Y
authors.lastname: Louzoun
authors.affiliation: Department of Mathematics and Mathematical Biosciences Institute, Ohio State University, Columbus, OH 43210, United States. Electronic address: cxue@math.osu.edu.
authors.forename: Chuan
authors.initials: C
authors.lastname: Xue
authors.affiliation: Internal Medicine, Ohio State University, Columbus, OH 43210, United States.
authors.forename: Gregory B
authors.initials: GB
authors.lastname: Lesinski
authors.affiliation: Department of Mathematics and Mathematical Biosciences Institute, Ohio State University, Columbus, OH 43210, United States.
authors.forename: Avner
authors.initials: A
authors.lastname: Friedman
mesh_terms: D049109:Cell Proliferation; D066246:ErbB Receptors / Q000235:genetics; D020868:Gene Silencing; D006801:Humans; D007167:Immunotherapy / Q000379:methods*; D018448:Models, Immunological; D010190:Pancreatic Neoplasms / Q000235:genetics / Q000276:immunology* / Q000473:pathology / Q000628:therapy; D011379:Prognosis; D012333:RNA, Messenger / Q000235:genetics; D016212:Transforming Growth Factor beta / Q000037:antagonists & inhibitors / Q000276:immunology; D019139:Tumor Escape / Q000276:immunology
chemical_list: D012333:RNA, Messenger; D016212:Transforming Growth Factor beta; D066246:ErbB Receptors
keywords: Immune response; Immunotherapy; Pancreatic cancer