Publication Date
2021
Journal or Book Title
Journal of Personalized Medicine
Abstract
Breast cancer is the most prominent type of cancer among women. Understanding the microenvironment of breast cancer and the interactions between cells and cytokines will lead to better treatment approaches for patients. In this study, we developed a data-driven mathematical model to investigate the dynamics of key cells and cytokines involved in breast cancer development. We used gene expression profiles of tumors to estimate the relative abundance of each immune cell and group patients based on their immune patterns. Dynamical results show the complex interplay between cells and molecules, and sensitivity analysis emphasizes the direct effects of macrophages and adipocytes on cancer cell growth. In addition, we observed the dual effect of IFN-γ" role="presentation" style="box-sizing: border-box; max-height: none; display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative;">γ on cancer proliferation, either through direct inhibition of cancer cells or by increasing the cytotoxicity of CD8+ T-cells.
DOI
https://doi.org/10.3390/jpm11101031
Volume
11
Issue
10
License
UMass Amherst Open Access Policy
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Mirzaei, Navi Mohammad; Su, Sumeyye; Sofia, Dilruba; Hegarty, Maura; Abel-Rahman, Mohamed H.; Asadpoure, Alireza; Cebulla, Colleen M.; Chang, Young Hwan; Hao, Wenrui; Jackson, Pamela R.; Lee, Adrian V.; Stover, Daniel G.; Tatarova, Zuzana; Zervantonakis, Ioannis K.; and Shahriyari, Leili, "A Mathematical Model of Breast Tumor Progression Based on Immune Infiltration" (2021). Journal of Personalized Medicine. 1317.
https://doi.org/10.3390/jpm11101031