@inproceedings{04f61b7050f94004bea7d0d093ac23f6,
title = "A mathematical model to study breast cancer growth",
abstract = "The aim of this paper is (i)to study breast cancer growth by mean of a mathematical model describing cell population dynamics during cancer growth, and (ii)to use this model to reproduce and explain experimental data. We started from a linear model describing cancer subpopulations evolution based on the Cancer Stem Cell (CSC) theory, and we added feedback mechanisms from the cell populations to mimic micro-environment effects in cancer growth. In details, we hypothesized two feedback mechanisms and we studied their effects both separately and combined together. In this way we obtained three new models that we tuned using data derived by TUBO Cancer cell line and describing the evolution of the total cell population and the subpopulations over time. Finally, we exploited these three models to understand which combination of feedback mechanisms better describe the experimental data.",
keywords = "Breast cancer growth model, Cancer Stem Cell theory and mathematical models",
author = "Giorgia Chivassa and Chiara Fornari and Roberta Sirovichr and Marzio Pennisi and Marco Beccuti and Francesca Cordero",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 ; Conference date: 13-11-2017 Through 16-11-2017",
year = "2017",
month = dec,
day = "15",
doi = "10.1109/BIBM.2017.8217874",
language = "English",
series = "Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1438--1445",
editor = "Illhoi Yoo and Zheng, {Jane Huiru} and Yang Gong and Hu, {Xiaohua Tony} and Chi-Ren Shyu and Yana Bromberg and Jean Gao and Dmitry Korkin",
booktitle = "Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017",
address = "United States",
}
