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Patient-Derived Xenograft Models for Endometrial Cancer Research

Endometrial cancer (EC) is the most common malignancy of the genital tract among women in developed countries. Recently, a molecular classification of EC has been performed providing a system that, in conjunction with histological observations, reliably improves EC classification and enhances patien...

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Autores principales: Moiola, Cristian P., Lopez-Gil, Carlos, Cabrera, Silvia, Garcia, Angel, Van Nyen, Tom, Annibali, Daniela, Fonnes, Tina, Vidal, August, Villanueva, Alberto, Matias-Guiu, Xavier, Krakstad, Camilla, Amant, Frédéric, Gil-Moreno, Antonio, Colas, Eva
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6121639/
https://www.ncbi.nlm.nih.gov/pubmed/30126113
http://dx.doi.org/10.3390/ijms19082431
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author Moiola, Cristian P.
Lopez-Gil, Carlos
Cabrera, Silvia
Garcia, Angel
Van Nyen, Tom
Annibali, Daniela
Fonnes, Tina
Vidal, August
Villanueva, Alberto
Matias-Guiu, Xavier
Krakstad, Camilla
Amant, Frédéric
Gil-Moreno, Antonio
Colas, Eva
author_facet Moiola, Cristian P.
Lopez-Gil, Carlos
Cabrera, Silvia
Garcia, Angel
Van Nyen, Tom
Annibali, Daniela
Fonnes, Tina
Vidal, August
Villanueva, Alberto
Matias-Guiu, Xavier
Krakstad, Camilla
Amant, Frédéric
Gil-Moreno, Antonio
Colas, Eva
author_sort Moiola, Cristian P.
collection PubMed
description Endometrial cancer (EC) is the most common malignancy of the genital tract among women in developed countries. Recently, a molecular classification of EC has been performed providing a system that, in conjunction with histological observations, reliably improves EC classification and enhances patient management. Patient-derived xenograft models (PDX) represent nowadays a promising tool for translational research, since they closely resemble patient tumour features and retain molecular and histological features. In EC, PDX models have already been used, mainly as an individualized approach to evaluate the efficacy of novel therapies and to identify treatment-response biomarkers; however, their uses in more global or holistic approaches are still missing. As a collaborative effort within the ENITEC network, here we describe one of the most extensive EC PDX cohorts developed from primary tumour and metastasis covering all EC subtypes. Our models are histologically and molecularly characterized and represent an excellent reservoir of EC tumour samples for translational research. This review compiles the information on current methods of EC PDX generation and their utility and provides new perspectives for the exploitation of these valuable tools in order to increase the success ratio for translating results to clinical practice.
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spelling pubmed-61216392018-09-07 Patient-Derived Xenograft Models for Endometrial Cancer Research Moiola, Cristian P. Lopez-Gil, Carlos Cabrera, Silvia Garcia, Angel Van Nyen, Tom Annibali, Daniela Fonnes, Tina Vidal, August Villanueva, Alberto Matias-Guiu, Xavier Krakstad, Camilla Amant, Frédéric Gil-Moreno, Antonio Colas, Eva Int J Mol Sci Review Endometrial cancer (EC) is the most common malignancy of the genital tract among women in developed countries. Recently, a molecular classification of EC has been performed providing a system that, in conjunction with histological observations, reliably improves EC classification and enhances patient management. Patient-derived xenograft models (PDX) represent nowadays a promising tool for translational research, since they closely resemble patient tumour features and retain molecular and histological features. In EC, PDX models have already been used, mainly as an individualized approach to evaluate the efficacy of novel therapies and to identify treatment-response biomarkers; however, their uses in more global or holistic approaches are still missing. As a collaborative effort within the ENITEC network, here we describe one of the most extensive EC PDX cohorts developed from primary tumour and metastasis covering all EC subtypes. Our models are histologically and molecularly characterized and represent an excellent reservoir of EC tumour samples for translational research. This review compiles the information on current methods of EC PDX generation and their utility and provides new perspectives for the exploitation of these valuable tools in order to increase the success ratio for translating results to clinical practice. MDPI 2018-08-17 /pmc/articles/PMC6121639/ /pubmed/30126113 http://dx.doi.org/10.3390/ijms19082431 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Moiola, Cristian P.
Lopez-Gil, Carlos
Cabrera, Silvia
Garcia, Angel
Van Nyen, Tom
Annibali, Daniela
Fonnes, Tina
Vidal, August
Villanueva, Alberto
Matias-Guiu, Xavier
Krakstad, Camilla
Amant, Frédéric
Gil-Moreno, Antonio
Colas, Eva
Patient-Derived Xenograft Models for Endometrial Cancer Research
title Patient-Derived Xenograft Models for Endometrial Cancer Research
title_full Patient-Derived Xenograft Models for Endometrial Cancer Research
title_fullStr Patient-Derived Xenograft Models for Endometrial Cancer Research
title_full_unstemmed Patient-Derived Xenograft Models for Endometrial Cancer Research
title_short Patient-Derived Xenograft Models for Endometrial Cancer Research
title_sort patient-derived xenograft models for endometrial cancer research
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6121639/
https://www.ncbi.nlm.nih.gov/pubmed/30126113
http://dx.doi.org/10.3390/ijms19082431
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