A mathematical model to study breast cancer growth

Giorgia Chivassa; Chiara Fornari; Roberta Sirovichr; Marzio Pennisi; Marco Beccuti; Francesca Cordero

doi:10.1109/BIBM.2017.8217874

A mathematical model to study breast cancer growth

Giorgia Chivassa
, Chiara Fornari
, Roberta Sirovichr
, Marzio Pennisi
, Marco Beccuti
, Francesca Cordero

Risultato della ricerca: Capitolo in libro/report/atti di convegno › Contributo a conferenza › peer review

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.

Lingua originale	Inglese
Titolo della pubblicazione ospite	Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Editor	Illhoi Yoo, Jane Huiru Zheng, Yang Gong, Xiaohua Tony Hu, Chi-Ren Shyu, Yana Bromberg, Jean Gao, Dmitry Korkin
Editore	Institute of Electrical and Electronics Engineers Inc.
Pagine	1438-1445
Numero di pagine	8
ISBN (elettronico)	9781509030491
DOI	https://doi.org/10.1109/BIBM.2017.8217874
Stato di pubblicazione	Pubblicato - 15 dic 2017
Pubblicato esternamente	Sì
Evento	2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 - Kansas City, United States Durata: 13 nov 2017 → 16 nov 2017

Serie di pubblicazioni

Nome	Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Volume	2017-January

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Paese/Territorio	United States
Città	Kansas City
Periodo	13/11/17 → 16/11/17

OSS delle Nazioni Unite

Questo processo contribuisce al raggiungimento dei seguenti obiettivi di sviluppo sostenibile

SDG 3 Salute e benessere

Accesso al documento

10.1109/BIBM.2017.8217874

Altri file e collegamenti

Link to publication in Scopus

Cita questo

Chivassa, G., Fornari, C., Sirovichr, R., Pennisi, M., Beccuti, M., & Cordero, F. (2017). A mathematical model to study breast cancer growth. In I. Yoo, J. H. Zheng, Y. Gong, X. T. Hu, C.-R. Shyu, Y. Bromberg, J. Gao, & D. Korkin (Edd.), Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 (pagg. 1438-1445). (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017; Vol. 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2017.8217874

Chivassa, Giorgia ; Fornari, Chiara ; Sirovichr, Roberta et al. / A mathematical model to study breast cancer growth. Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. curatore / Illhoi Yoo ; Jane Huiru Zheng ; Yang Gong ; Xiaohua Tony Hu ; Chi-Ren Shyu ; Yana Bromberg ; Jean Gao ; Dmitry Korkin. Institute of Electrical and Electronics Engineers Inc., 2017. pagg. 1438-1445 (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017).

@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",

}

Chivassa, G, Fornari, C, Sirovichr, R, Pennisi, M, Beccuti, M & Cordero, F 2017, A mathematical model to study breast cancer growth. in I Yoo, JH Zheng, Y Gong, XT Hu, C-R Shyu, Y Bromberg, J Gao & D Korkin (edd.), Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017, vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pagg. 1438-1445, 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017, Kansas City, United States, 13/11/17. https://doi.org/10.1109/BIBM.2017.8217874

A mathematical model to study breast cancer growth. / Chivassa, Giorgia; Fornari, Chiara; Sirovichr, Roberta et al.
Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. a cura di / Illhoi Yoo; Jane Huiru Zheng; Yang Gong; Xiaohua Tony Hu; Chi-Ren Shyu; Yana Bromberg; Jean Gao; Dmitry Korkin. Institute of Electrical and Electronics Engineers Inc., 2017. pag. 1438-1445 (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017; Vol. 2017-January).

Risultato della ricerca: Capitolo in libro/report/atti di convegno › Contributo a conferenza › peer review

TY - GEN

T1 - A mathematical model to study breast cancer growth

AU - Chivassa, Giorgia

AU - Fornari, Chiara

AU - Sirovichr, Roberta

AU - Pennisi, Marzio

AU - Beccuti, Marco

AU - Cordero, Francesca

PY - 2017/12/15

Y1 - 2017/12/15

N2 - 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.

AB - 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.

KW - Breast cancer growth model

KW - Cancer Stem Cell theory and mathematical models

UR - https://www.scopus.com/pages/publications/85045991585

U2 - 10.1109/BIBM.2017.8217874

DO - 10.1109/BIBM.2017.8217874

M3 - Conference contribution

AN - SCOPUS:85045991585

T3 - Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017

SP - 1438

EP - 1445

BT - Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017

A2 - Yoo, Illhoi

A2 - Zheng, Jane Huiru

A2 - Gong, Yang

A2 - Hu, Xiaohua Tony

A2 - Shyu, Chi-Ren

A2 - Bromberg, Yana

A2 - Gao, Jean

A2 - Korkin, Dmitry

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017

Y2 - 13 November 2017 through 16 November 2017

ER -

Chivassa G, Fornari C, Sirovichr R, Pennisi M, Beccuti M, Cordero F. A mathematical model to study breast cancer growth. In Yoo I, Zheng JH, Gong Y, Hu XT, Shyu CR, Bromberg Y, Gao J, Korkin D, editor, Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. Institute of Electrical and Electronics Engineers Inc. 2017. pag. 1438-1445. (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017). doi: 10.1109/BIBM.2017.8217874

A mathematical model to study breast cancer growth

Abstract

Serie di pubblicazioni

???event.eventtypes.event.conference???

OSS delle Nazioni Unite

Accesso al documento

Altri file e collegamenti

Fingerprint

Cita questo