Publication Date
2020
Journal or Book Title
Journal of Clinical Medicine
Abstract
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. For instance, in tumors with a smaller density of naive macrophages than activated macrophages, a higher activation rate of macrophages leads to an increase in cancer cell density, demonstrating a negative effect of macrophages. Other tumors however, exhibit an opposite trend, showing a positive effect of macrophages in controlling tumor size. Although the results indicate that for all patients the size of the tumor is sensitive to the parameters related to macrophages, such as their activation and death rate, this research demonstrates that no single biomarker could predict the dynamics of tumors
DOI
https://doi.org/10.3390/jcm9123947
Volume
9
Special Issue
Latest Developments in Mathematical Oncology and Cancer Systems Biology
Issue
12
License
UMass Amherst Open Access Policy
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Kirshtein, Arkadz; Akbarinejad, Shaya; Hao, Wenrui; Le, Trang; Su, Sumeyye; Aronow, Rachel A.; and Shahriyari, Leili, "Data Driven Mathematical Model of Colon Cancer Progression" (2020). Journal of Clinical Medicine. 1305.
https://doi.org/10.3390/jcm9123947