BackgroundOrthotopic endometrial cancer models provide a unique tool for studies of tumour growth and metastatic spread. Novel preclinical imaging methods also have the potential to quantify functional tumour characteristics in vivo, with potential relevance for monitoring response to therapy.MethodsAfter orthotopic injection with luc-expressing endometrial cancer cells, eleven mice developed disease detected by weekly bioluminescence imaging (BLI). In parallel the same mice underwent positron emission tomography–computed tomography (PET-CT) and magnetic resonance imaging (MRI) employing 18F-fluorodeoxyglocose (18F-FDG) or 18F- fluorothymidine (18F-FLT) and contrast reagent, respectively. The mice were sacrificed when moribund, and post-mortem examination included macroscopic and microscopic examination for validation of growth of primary uterine tumours and metastases. PET-CT was also performed on a patient derived model (PDX) generated from a patient with grade 3 endometrioid endometrial cancer.ResultsIncreased BLI signal during tumour growth was accompanied by increasing metabolic tumour volume (MTV) and increasing MTV x mean standard uptake value of the tumour (SUVmean) in 18F-FDG and 18F-FLT PET-CT, and MRI conspicuously depicted the uterine tumour. At necropsy 82% (9/11) of the mice developed metastases detected by the applied imaging methods. 18F-FDG PET proved to be a good imaging method for detection of patient derived tumour tissue.ConclusionsWe demonstrate that all imaging modalities enable monitoring of tumour growth and metastatic spread in an orthotopic mouse model of endometrial carcinoma. Both PET tracers, 18F-FDG and 18F-FLT, appear to be equally feasible for detecting tumour development and represent, together with MRI, promising imaging tools for monitoring of patient-derived xenograft (PDX) cancer models.
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.
Background A major hurdle in translational endometrial cancer (EC) research is the lack of robust preclinical models that capture both inter- and intra-tumor heterogeneity. This has hampered the development of new treatment strategies for people with EC. Methods EC organoids were derived from resected patient tumor tissue and expanded in a chemically defined medium. Established EC organoids were orthotopically implanted into female NSG mice. Patient tissue and corresponding models were characterized by morphological evaluation, biomarker and gene expression and by whole exome sequencing. A gene signature was defined and its prognostic value was assessed in multiple EC cohorts using Mantel-Cox (log-rank) test. Response to carboplatin and/or paclitaxel was measured in vitro and evaluated in vivo. Statistical difference between groups was calculated using paired t-test. Results We report EC organoids established from EC patient tissue, and orthotopic organoid-based patient-derived xenograft models (O-PDXs). The EC organoids and O-PDX models mimic the tissue architecture, protein biomarker expression and genetic profile of the original tissue. Organoids show heterogenous sensitivity to conventional chemotherapy, and drug response is reproduced in vivo. The relevance of these models is further supported by the identification of an organoid-derived prognostic gene signature. This signature is validated as prognostic both in our local patient cohorts and in the TCGA endometrial cancer cohort. Conclusions We establish robust model systems that capture both the diversity of endometrial tumors and intra-tumor heterogeneity. These models are highly relevant preclinical tools for the elucidation of the molecular pathogenesis of EC and identification of potential treatment strategies.
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