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dc.contributor.author
Serrano, Alejandro  
dc.contributor.author
Zalba, Sara  
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Lasarte, Juan Jose  
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Troconiz, Iñaki F.  
dc.contributor.author
Riva, Natalia  
dc.contributor.author
Garrido, Maria J.  
dc.date.available
2025-04-28T09:22:55Z  
dc.date.issued
2024-11  
dc.identifier.citation
Serrano, Alejandro; Zalba, Sara; Lasarte, Juan Jose; Troconiz, Iñaki F.; Riva, Natalia; et al.; Quantitative Approach to Explore Regulatory T Cell Activity in Immuno-Oncology; MDPI; Pharmaceutics; 16; 11; 11-2024; 1-18  
dc.identifier.issn
1999-4923  
dc.identifier.uri
http://hdl.handle.net/11336/259690  
dc.description.abstract
The failure of immunotherapies in cancer patients is being widely studied due to the complexitiespresent in the tumor microenvironment (TME), where regulatory T cells (Treg) appear toactively participate in providing an immune escape mechanism for tumors. Therefore, therapies tospecifically inhibit tumor-infiltrating Treg represent a challenge, because Treg are distributedthroughout the body and provide physiological immune homeostasis to prevent autoimmune diseases.Characterization of immunological and functional profiles could help to identify the mechanismsthat need to be inhibited or activated to ensure Treg modulation in the tumor. To addressthis, quantitative in silico approaches based on mechanistic mathematical models integrating multiscaleinformation from immune and tumor cells and the effect of different therapies have allowedthe building of computational frameworks to simulate different hypotheses, some of which havesubsequently been experimentally validated. Therefore, this review presents a list of diverse computationalmathematical models that examine the role of Treg as a crucial immune resistance mechanismcontributing to the failure of immunotherapy. In addition, this review highlights the relevanceof certain molecules expressed in Treg that are associated with the TME immunosuppression,which could be incorporated into the mathematical model for a better understanding of the contributionof Treg modulation. Finally, different preclinical and clinical combinations of molecules arealso included to show the trend of new therapies targeting Treg.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
MDPI  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by/2.5/ar/  
dc.subject
TREG CELLS  
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QSP MODEL  
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IMMUNOTHERAPY  
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TUMOR GROWTH DYNAMICS  
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Otras Ciencias de la Computación e Información  
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Ciencias de la Computación e Información  
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CIENCIAS NATURALES Y EXACTAS  
dc.title
Quantitative Approach to Explore Regulatory T Cell Activity in Immuno-Oncology  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2025-04-25T10:44:00Z  
dc.journal.volume
16  
dc.journal.number
11  
dc.journal.pagination
1-18  
dc.journal.pais
Suiza  
dc.journal.ciudad
Basel  
dc.description.fil
Fil: Serrano, Alejandro. Universidad de Navarra. Facultad de Farmacia y Nutricion.; España  
dc.description.fil
Fil: Zalba, Sara. Universidad de Navarra. Facultad de Farmacia y Nutricion.; España  
dc.description.fil
Fil: Lasarte, Juan Jose. Universidad de Navarra. Facultad de Farmacia y Nutricion.; España  
dc.description.fil
Fil: Troconiz, Iñaki F.. Universidad de Navarra. Facultad de Farmacia y Nutricion.; España  
dc.description.fil
Fil: Riva, Natalia. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina  
dc.description.fil
Fil: Garrido, Maria J.. Universidad de Navarra. Facultad de Farmacia y Nutricion.; España  
dc.journal.title
Pharmaceutics  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/1999-4923/16/11/1461  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.3390/pharmaceutics16111461