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

doi:10.3390/jpm11101031

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 journal › Article › peer-review

16 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 language	English (US)
Article number	1031
Journal	Journal of Personalized Medicine
Volume	11
Issue number	10
DOIs	https://doi.org/10.3390/jpm11101031
State	Published - 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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10.3390/jpm11101031

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Mirzaei, N. M., Su, S., Sofia, D., Hegarty, M., Abdel-Rahman, M. H., Asadpoure, A., Cebulla, C. M., Chang, Y. H., Hao, W., Jackson, P. R., Lee, A. V., Stover, D. G., Tatarova, Z., Zervantonakis, I. K., & Shahriyari, L. (2021). A mathematical model of breast tumor progression based on immune infiltration. Journal of Personalized Medicine, 11(10), Article 1031. https://doi.org/10.3390/jpm11101031

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title = "A mathematical model of breast tumor progression based on immune infiltration",

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.",

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

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

note = "Publisher Copyright: {\textcopyright} 2021 by the authors. Licensee MDPI, Basel, Switzerland.",

year = "2021",

month = oct,

doi = "10.3390/jpm11101031",

language = "English (US)",

volume = "11",

journal = "Journal of Personalized Medicine",

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AU - Mirzaei, Navid Mohammad

AU - Su, Sumeyye

AU - Sofia, Dilruba

AU - Hegarty, Maura

AU - Abdel-Rahman, Mohamed H.

AU - Asadpoure, Alireza

AU - Cebulla, Colleen M.

AU - Chang, Young Hwan

AU - Hao, Wenrui

AU - Jackson, Pamela R.

AU - Lee, Adrian V.

AU - Stover, Daniel G.

AU - Tatarova, Zuzana

AU - Zervantonakis, Ioannis K.

AU - Shahriyari, Leili

PY - 2021/10

Y1 - 2021/10

N2 - 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.

AB - 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.

KW - Adipocytes

KW - Breast cancer

KW - Cytokines

KW - Data driven mathematical model

KW - Estrogen

KW - HMGB1

KW - IFN-γ

KW - Immune infiltration

KW - Macrophages

KW - Ordinary differential equations

KW - Sensitivity analysis

KW - T-cells

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JF - Journal of Personalized Medicine

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A mathematical model of breast tumor progression based on immune infiltration

Abstract

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