A mathematical model of breast tumor progression based on immune infiltration

Navid Mohammad Mirzaei, Sumeyye Su, Dilruba Sofia, Maura Hegarty, Mohamed H. Abdel-Rahman, Alireza Asadpoure, Colleen M. Cebulla, Young Hwan Chang, Wenrui Hao, Pamela R. Jackson, Adrian V. Lee, Daniel G. Stover, Zuzana Tatarova, Ioannis K. Zervantonakis, Leili Shahriyari

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

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 on cancer proliferation, either through direct inhibition of cancer cells or by increasing the cytotoxicity of CD8+ T-cells.

Original languageEnglish (US)
Article number1031
JournalJournal of Personalized Medicine
Volume11
Issue number10
DOIs
StatePublished - Oct 2021

Keywords

  • Adipocytes
  • Breast cancer
  • Cytokines
  • Data driven mathematical model
  • Estrogen
  • HMGB1
  • IFN-γ
  • Immune infiltration
  • Macrophages
  • Ordinary differential equations
  • Sensitivity analysis
  • T-cells

ASJC Scopus subject areas

  • Medicine (miscellaneous)

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