Dataset Information

Hu2019 - Modeling Pancreatic Cancer Dynamics with Immunotherapy

ABSTRACT: This is a mathematical model of pancreatic cancer that includes descriptions of pancreatic cancer cells, pancreatic stellate cells, effector cells and tumor-promoting and tumor-suppressing cytokines to investigate the effects of immunotherapies on patient survival.

SUBMITTER: Johannes Meyer

PROVIDER: BIOMD0000000792 | BioModels | 2024-09-02

REPOSITORIES: BioModels

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Dataset's files

Source:

			Action	DRS
	BIOMD0000000792?filename=Hu2019-biopax2.owl	Owl
	BIOMD0000000792?filename=Hu2019-biopax3.owl	Owl
	BIOMD0000000792?filename=Hu2019-matlab.m	Other
	BIOMD0000000792?filename=Hu2019-octave.m	Other
	BIOMD0000000792?filename=Hu2019.cps	Other

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Publications

Modeling Pancreatic Cancer Dynamics with Immunotherapy.

Hu Xiaochuan X Ke Guoyi G Jang Sophia R-J SR

Bulletin of mathematical biology 20190306 6

We develop a mathematical model of pancreatic cancer that includes pancreatic cancer cells, pancreatic stellate cells, effector cells and tumor-promoting and tumor-suppressing cytokines to investigate the effects of immunotherapies on patient survival. The model is first validated using the survival data of two clinical trials. Local sensitivity analysis of the parameters indicates there exists a critical activation rate of pro-tumor cytokines beyond which the cancer can be eradicated if four ad ...[more]

PMID: 30843136

Similar Datasets

Project description:The paper describes a model on the size of pancreatic tumour. Created by COPASI 4.25 (Build 207) This model is described in the article: Modeling Pancreatic Cancer Dynamics with Immunotherapy Xiaochuan Hu, Guoyi Ke and Sophia R.-J. Jang Bulletin of Mathematical Biology (2019) 81:1885–1915 Abstract: We develop a mathematical model of pancreatic cancer that includes pancreatic cancer cells, pancreatic stellate cells, effector cells and tumor-promoting and tumor- suppressing cytokines to investigate the effects of immunotherapies on patient survival. The model is first validated using the survival data of two clinical trials. Local sen- sitivity analysis of the parameters indicates there exists a critical activation rate of pro-tumor cytokines beyond which the cancer can be eradicated if four adoptive trans- fers of immune cells are applied. Optimal control theory is explored as a potential tool for searching the best adoptive cellular immunotherapies. Combined immunother- apies between adoptive ex vivo expanded immune cells and TGF-β inhibition by siRNA treatments are investigated. This study concludes that mono-immunotherapy is unlikely to control the pancreatic cancer and combined immunotherapies between anti-TGF-β and adoptive transfers of immune cells can prolong patient survival. We show through numerical explorations that how these two types of immunotherapies are scheduled is important to survival. Applying TGF-β inhibition first followed by adoptive immune cell transfers can yield better survival outcomes. This model is hosted on BioModels Database and identified by: MODEL1907050003. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.