Patient-Derived Xenograft Models for Endometrial Cancer Research

Abstract

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 andmetastasis covering all EC subtypes. Ourmodels are histologically andmolecularly 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.

This work was supported by CIBERONC (CB16/12/00328), the “Fondo Europeo de Desarrollo Regional” FEDER (RTC-2015-3821-1), Grups consolidats de la Generalitat de Catalunya (2017 SGR-1661) and the Instituto de Salud Carlos III (PI14/02043; PI17/02071). An AGAUR grant funded CL-G (2018FI_B_00573), and a PERIS grant funded EC (SLT002/16/00315) from Generalitat de Catalunya. The present work has been also funded by the “Fonds National de la Recherche du Luxembourg” (FNR) via the PEARL-CPIL program to BD and an AFR grant to AL (PDR 2013-2, Project Reference 6835664).