Feasibility and utility of MRI and dynamic 18F-FDG-PET in an orthotopic organoid-based patient-derived mouse model of endometrial cancer.

BACKGROUND: Pelvic magnetic resonance imaging (MRI) and whole-body positron emission tomography-computed tomography (PET-CT) play an important role at primary diagnostic work-up and in detecting recurrent disease in endometrial cancer (EC) patients, however the preclinical use of these imaging methods is currently limited. We demonstrate the feasibility and utility of MRI and dynamic 18F-fluorodeoxyglucose (FDG)-PET imaging for monitoring tumor progression and assessing chemotherapy response in an orthotopic organoid-based patient-derived xenograft (O-PDX) mouse model of EC. METHODS: 18 O-PDX mice (grade 3 endometrioid EC, stage IIIC1), selectively underwent weekly T2-weighted MRI (total scans = 32), diffusion-weighted MRI (DWI) (total scans = 9) and dynamic 18F-FDG-PET (total scans = 26) during tumor progression. MRI tumor volumes (vMRI), tumor apparent diffusion coefficient values (ADCmean) and metabolic tumor parameters from 18F-FDG-PET including maximum and mean standard uptake values (SUVmax/SUVmean), metabolic tumor volume (MTV), total lesion glycolysis (TLG) and metabolic rate of 18F-FDG (MRFDG) were calculated. Further, nine mice were included in a chemotherapy treatment study (treatment; n = 5, controls; n = 4) and tumor ADCmean-values were compared to changes in vMRI and cellular density from histology at endpoint. A Mann-Whitney test was used to evaluate differences between groups. RESULTS: Tumors with large tumor volumes (vMRI) had higher metabolic activity (MTV and TLG) in a clear linear relationship (r2 = 0.92 and 0.89, respectively). Non-invasive calculation of MRFDG from dynamic 18F-FDG-PET (mean MRFDG = 0.39 µmol/min) was feasible using an image-derived input function. Treated mice had higher tumor ADCmean (p = 0.03), lower vMRI (p = 0.03) and tumor cellular density (p = 0.02) than non-treated mice, all indicating treatment response. CONCLUSION: Preclinical imaging mirroring clinical imaging methods in EC is highly feasible for monitoring tumor progression and treatment response in the present orthotopic organoid mouse model.

Asparaginase-like protein 1 is an independent prognostic marker in primary endometrial cancer, and is frequently lost in metastatic lesions.

OBJECTIVE: Loss of Asparaginase-like protein 1 (ASRGL1) has been suggested as a prognostic biomarker in endometrial carcinoma. Our objective was to validate this in a prospectively collected, independent patient cohort, and evaluate ASRGL1 expression in endometrial carcinoma precursor lesion and metastases. METHODS: 782 primary endometrial carcinomas, 90 precursor lesions (complex atypical hyperplasia), and 179 metastases (from 87 patients) were evaluated for ASRGL1 expression by immunohistochemistry in relation to clinical and histopathological data. ASRGL1 mRNA level was investigated in 237 primary tumors and related to survival and ASRGL1 protein expression. RESULTS: Low expression of ASRGL1 protein and ASRGL1 mRNA predicted poor disease specific survival (P<0.001). In multivariate survival analyses ASRGL1 had independent prognostic value both in the whole patient cohort (Hazard ratio (HR): 1.53, 95% confidence interval (CI): 1.04-2.26, P=0.031) and within the endometrioid subgroup (HR: 2.64, CI: 1.47-4.74, P=0.001). Low ASRGL1 expression was less frequent in patients with low grade endometrioid primary tumors compared to high grade endometrioid and non-endometrioid primary tumors, and ASRGL1 was lost in the majority of metastatic lesions. CONCLUSIONS: In a prospective setting ASRGL1 validates as a strong prognostic biomarker in endometrial carcinoma. Loss of ASRGL1 is associated with aggressive disease and poor survival, and is demonstrated for the first time to have independent prognostic value in the entire endometrial carcinoma patient population.

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 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.

Cancer awareness in the general population varies with sex, age and media coverage: A population-based survey with focus on gynecologic cancers.

OBJECTIVES: There is a need for more knowledge about the public awareness and attitudes towards gynecologic cancers. We employed a research-purpose population-based citizen panel to assess how often people recall gynecologic cancers compared to other cancer types and to explore the relative importance of different information channels in relaying cancer information. STUDY DESIGN: We conducted an online survey using the Norwegian Citizen Panel (n = 1441 respondents), exploring associations between demographic factors and frequency of mentioning specific cancer types. We also searched The Norwegian Media Archive to assess the media coverage of different cancer types. Factors affecting likelihood of mentioning different cancers were assessed by multivariate regression. RESULTS: Only 41 % of respondents listed one or more cancers in female genital organs. Of the gynecological cancers, cervical cancer was most frequently mentioned (28 %), followed by ovarian (12 %) and endometrial cancer (11 %). Female responders were more likely to mention cervical (OR 2.47, 95 % CI 2.16-2.78) and ovarian cancer (OR 2.09, 95 % CI 1.60-2.58) than male responders, but not endometrial cancer. Family and friends who have had cancer (50 %) and different types of media coverage (41 %) were reported as the most common sources of cancer information. The three most frequently mentioned cancer types in our survey were breast (77 %), hematologic (76 %) and lung cancer (75 %), which also were the cancer types having most media coverage. CONCLUSIONS: Gynecological cancers are less frequently mentioned by Norwegian citizens when compared to several other cancer types such as breast-, hematologic- and lung cancer. Sex and age are important factors that affect awareness of cancer types. Media is likely to play an important role in what cancer types the public recalls.

Patient-derived organoids reflect the genetic profile of endometrial tumors and predict patient prognosis.

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.

Erratum: Author Correction: Patient-derived organoids reflect the genetic profile of endometrial tumors and predict patient prognosis.

[This corrects the article DOI: 10.1038/s43856-021-00019-x.].

Near-Infrared Fluorescent Imaging for Monitoring of Treatment Response in Endometrial Carcinoma Patient-Derived Xenograft Models.

Imaging of clinically relevant preclinical animal models is critical to the development of personalized therapeutic strategies for endometrial carcinoma. Although orthotopic patient-derived xenografts (PDXs) reflecting heterogeneous molecular subtypes are considered the most relevant preclinical models, their use in therapeutic development is limited by the lack of appropriate imaging modalities. Here, we describe molecular imaging of a near-infrared fluorescently labeled monoclonal antibody targeting epithelial cell adhesion molecule (EpCAM) as an in vivo imaging modality for visualization of orthotopic endometrial carcinoma PDX. Application of this near-infrared probe (EpCAM-AF680) enabled both spatio-temporal visualization of development and longitudinal therapy monitoring of orthotopic PDX. Notably, EpCAM-AF680 facilitated imaging of multiple PDX models representing different subtypes of the disease. Thus, the combined implementation of EpCAM-AF680 and orthotopic PDX models creates a state-of-the-art preclinical platform for identification and validation of new targeted therapies and corresponding response predicting markers for endometrial carcinoma.

Imaging of Preclinical Endometrial Cancer Models for Monitoring Tumor Progression and Response to Targeted Therapy.

Endometrial cancer is the most common gynecologic malignancy in industrialized countries. Most patients are cured by surgery; however, about 15% of the patients develop recurrence with limited treatment options. Patient-derived tumor xenograft (PDX) mouse models represent useful tools for preclinical evaluation of new therapies and biomarker identification. Preclinical imaging by magnetic resonance imaging (MRI), positron emission tomography-computed tomography (PET-CT), single-photon emission computed tomography (SPECT) and optical imaging during disease progression enables visualization and quantification of functional tumor characteristics, which may serve as imaging biomarkers guiding targeted therapies. A critical question, however, is whether the in vivo model systems mimic the disease setting in patients to such an extent that the imaging biomarkers may be translatable to the clinic. The primary objective of this review is to give an overview of current and novel preclinical imaging methods relevant for endometrial cancer animal models. Furthermore, we highlight how these advanced imaging methods depict pathogenic mechanisms important for tumor progression that represent potential targets for treatment in endometrial cancer.

Multimodal Imaging of Orthotopic Mouse Model of Endometrial Carcinoma.

BACKGROUND: Orthotopic 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. METHODS: After 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. RESULTS: Increased 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. CONCLUSIONS: We 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.