Every colon cancer has its own unique characteristics, and therefore may respond differently to identical treatments. Here, we develop a data driven mathematical model for the interaction network of key components of immune microenvironment in colon cancer. We estimate the relative abundance of each immune cell from gene expression profiles of tumors, and group patients based on their immune patterns. Then we compare the tumor sensitivity and progression in each of these groups of patients, and observe differences in the patterns of tumor growth between the groups.
This repository contains the following scripts:
qspmodel.py: python classes and methods for analysis of Mathematical model of immune response in cancer
QSPClusterAnalysis.py: python script for analysis of parameter sensitivity and dynamics of Mathematical model of immune response in colon cancer
ParseQSPData.m: MatLab script to parse the results obtained by running QSPClusterAnalysis.py for ploting by PlotQSPData.m
PlotQSPData.m: MatLab script for plotting the results obtained by running QSPClusterAnalysis.py and ParseQSPData.m
If using any parts of this code please cite
A. Kirshtein, S. Akbarinejad, W. Hao, T. Le, S. Su, R. Aronow, L. Shahriyari, Data driven mathematical model of colon cancer progression, Journal of Clinical Medicine, 2020.