Prediction of anti-CD25 and 5-FU treatments efficacy for pancreatic cancer using a mathematical model

Abstract Background Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease with rising incidence and with 5-years overall survival of less than 8%. PDAC creates an immune-suppressive tumor microenvironment to escape immune-mediated eradication. Regulatory T (Treg) cells and myeloid-deriv...

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Autores principales:	Sajad Shafiekhani, Hojat Dehghanbanadaki, Azam Sadat Fatemi, Sara Rahbar, Jamshid Hadjati, Amir Homayoun Jafari
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	5-FU Anti-CD25 GUI Fuzzy ODE Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/a2604ce40f084ba89a35729eb57b16c3
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spelling	oai:doaj.org-article:a2604ce40f084ba89a35729eb57b16c32021-11-21T12:30:22ZPrediction of anti-CD25 and 5-FU treatments efficacy for pancreatic cancer using a mathematical model10.1186/s12885-021-08770-z1471-2407https://doaj.org/article/a2604ce40f084ba89a35729eb57b16c32021-11-01T00:00:00Zhttps://doi.org/10.1186/s12885-021-08770-zhttps://doaj.org/toc/1471-2407Abstract Background Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease with rising incidence and with 5-years overall survival of less than 8%. PDAC creates an immune-suppressive tumor microenvironment to escape immune-mediated eradication. Regulatory T (Treg) cells and myeloid-derived suppressor cells (MDSC) are critical components of the immune-suppressive tumor microenvironment. Shifting from tumor escape or tolerance to elimination is the major challenge in the treatment of PDAC. Results In a mathematical model, we combine distinct treatment modalities for PDAC, including 5-FU chemotherapy and anti- CD25 immunotherapy to improve clinical outcome and therapeutic efficacy. To address and optimize 5-FU and anti- CD25 treatment (to suppress MDSCs and Tregs, respectively) schedule in-silico and simultaneously unravel the processes driving therapeutic responses, we designed an in vivo calibrated mathematical model of tumor-immune system (TIS) interactions. We designed a user-friendly graphical user interface (GUI) unit which is configurable for treatment timings to implement an in-silico clinical trial to test different timings of both 5-FU and anti- CD25 therapies. By optimizing combination regimens, we improved treatment efficacy. In-silico assessment of 5-FU and anti- CD25 combination therapy for PDAC significantly showed better treatment outcomes when compared to 5-FU and anti- CD25 therapies separately. Due to imprecise, missing, or incomplete experimental data, the kinetic parameters of the TIS model are uncertain that this can be captured by the fuzzy theorem. We have predicted the uncertainty band of cell/cytokines dynamics based on the parametric uncertainty, and we have shown the effect of the treatments on the displacement of the uncertainty band of the cells/cytokines. We performed global sensitivity analysis methods to identify the most influential kinetic parameters and simulate the effect of the perturbation on kinetic parameters on the dynamics of cells/cytokines. Conclusion Our findings outline a rational approach to therapy optimization with meaningful consequences for how we effectively design treatment schedules (timing) to maximize their success, and how we treat PDAC with combined 5-FU and anti- CD25 therapies. Our data revealed that a synergistic combinatorial regimen targeting the Tregs and MDSCs in both crisp and fuzzy settings of model parameters can lead to tumor eradication.Sajad ShafiekhaniHojat DehghanbanadakiAzam Sadat FatemiSara RahbarJamshid HadjatiAmir Homayoun JafariBMCarticle5-FUAnti-CD25GUIFuzzyODENeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENBMC Cancer, Vol 21, Iss 1, Pp 1-21 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	5-FU Anti-CD25 GUI Fuzzy ODE Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
spellingShingle	5-FU Anti-CD25 GUI Fuzzy ODE Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Sajad Shafiekhani Hojat Dehghanbanadaki Azam Sadat Fatemi Sara Rahbar Jamshid Hadjati Amir Homayoun Jafari Prediction of anti-CD25 and 5-FU treatments efficacy for pancreatic cancer using a mathematical model
description	Abstract Background Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease with rising incidence and with 5-years overall survival of less than 8%. PDAC creates an immune-suppressive tumor microenvironment to escape immune-mediated eradication. Regulatory T (Treg) cells and myeloid-derived suppressor cells (MDSC) are critical components of the immune-suppressive tumor microenvironment. Shifting from tumor escape or tolerance to elimination is the major challenge in the treatment of PDAC. Results In a mathematical model, we combine distinct treatment modalities for PDAC, including 5-FU chemotherapy and anti- CD25 immunotherapy to improve clinical outcome and therapeutic efficacy. To address and optimize 5-FU and anti- CD25 treatment (to suppress MDSCs and Tregs, respectively) schedule in-silico and simultaneously unravel the processes driving therapeutic responses, we designed an in vivo calibrated mathematical model of tumor-immune system (TIS) interactions. We designed a user-friendly graphical user interface (GUI) unit which is configurable for treatment timings to implement an in-silico clinical trial to test different timings of both 5-FU and anti- CD25 therapies. By optimizing combination regimens, we improved treatment efficacy. In-silico assessment of 5-FU and anti- CD25 combination therapy for PDAC significantly showed better treatment outcomes when compared to 5-FU and anti- CD25 therapies separately. Due to imprecise, missing, or incomplete experimental data, the kinetic parameters of the TIS model are uncertain that this can be captured by the fuzzy theorem. We have predicted the uncertainty band of cell/cytokines dynamics based on the parametric uncertainty, and we have shown the effect of the treatments on the displacement of the uncertainty band of the cells/cytokines. We performed global sensitivity analysis methods to identify the most influential kinetic parameters and simulate the effect of the perturbation on kinetic parameters on the dynamics of cells/cytokines. Conclusion Our findings outline a rational approach to therapy optimization with meaningful consequences for how we effectively design treatment schedules (timing) to maximize their success, and how we treat PDAC with combined 5-FU and anti- CD25 therapies. Our data revealed that a synergistic combinatorial regimen targeting the Tregs and MDSCs in both crisp and fuzzy settings of model parameters can lead to tumor eradication.
format	article
author	Sajad Shafiekhani Hojat Dehghanbanadaki Azam Sadat Fatemi Sara Rahbar Jamshid Hadjati Amir Homayoun Jafari
author_facet	Sajad Shafiekhani Hojat Dehghanbanadaki Azam Sadat Fatemi Sara Rahbar Jamshid Hadjati Amir Homayoun Jafari
author_sort	Sajad Shafiekhani
title	Prediction of anti-CD25 and 5-FU treatments efficacy for pancreatic cancer using a mathematical model
title_short	Prediction of anti-CD25 and 5-FU treatments efficacy for pancreatic cancer using a mathematical model
title_full	Prediction of anti-CD25 and 5-FU treatments efficacy for pancreatic cancer using a mathematical model
title_fullStr	Prediction of anti-CD25 and 5-FU treatments efficacy for pancreatic cancer using a mathematical model
title_full_unstemmed	Prediction of anti-CD25 and 5-FU treatments efficacy for pancreatic cancer using a mathematical model
title_sort	prediction of anti-cd25 and 5-fu treatments efficacy for pancreatic cancer using a mathematical model
publisher	BMC
publishDate	2021
url	https://doaj.org/article/a2604ce40f084ba89a35729eb57b16c3
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Prediction of anti-CD25 and 5-FU treatments efficacy for pancreatic cancer using a mathematical model

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