Despite successful implementation of drugs targeting the human epidermal growth factor receptor 2 (HER2) receptor in breast and gastric cancers, the potential of HER2 as a therapeutic target in other cancers has been less studied, including endometrial cancer. We investigated expression levels of HER2 (ERBB2) in a large cohort of endometrial cancer lesions, also including complex atypical hyperplasia and metastatic lesions. 67 precursor lesions, 790 primary endometrial cancers and 383 metastatic lesions were investigated for HER2 expression in relation to clinicopathologic features and outcome. Protein levels were assessed by immunohistochemistry (using the HercepTest and staining index (SI) criteria), mRNA levels by microarrays and amplification status by chromogenic in situ hybridisation. High HER2 protein levels were significantly associated with features of aggressive disease and increased mRNA ERBB2 levels. HER2 expression defined by the SI proved to be a better predictor of survival compared with the HercepTest. A discordant HER2 expression pattern between paired primary and metastatic lesions was detected, revealing substantial reduction in HER2 expression from primary to metastatic disease. Loss of HER2 expression is common in metastatic endometrial cancer lesions and assessment of HER2 levels in the metastatic lesions may be important to define the potential benefit of anti-HER2 treatments in endometrial cancer patients.

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.

Prognostication is critical for accurate diagnosis and tailored treatment in endometrial cancer (EC). We employed radiogenomics to integrate preoperative magnetic resonance imaging (MRI, n = 487 patients) with histologic-, transcriptomic- and molecular biomarkers (n = 550 patients) aiming to identify aggressive tumor features in a study including 866 EC patients. Whole-volume tumor radiomic profiling from manually (radiologists) segmented tumors (n = 138 patients) yielded clusters identifying patients with high-risk histological features and poor survival. Radiomic profiling by a fully automated machine learning (ML)-based tumor segmentation algorithm (n = 336 patients) reproduced the same radiomic prognostic groups. From these radiomic risk-groups, an 11-gene high-risk signature was defined, and its prognostic role was reproduced in orthologous validation cohorts (n = 554 patients) and aligned with The Cancer Genome Atlas (TCGA) molecular class with poor survival (copy-number-high/p53-altered). We conclude that MRI-based integrated radiogenomics profiling provides refined tumor characterization that may aid in prognostication and guide future treatment strategies in EC.

Background: The endometrial cancer mismatch repair (MMR) deficient subgroup is defined by loss of MSH6, MSH2, PMS2 or MLH1. We compare MMR status in paired preoperative and operative samples and investigate the prognostic impact of differential MMR protein expression levels. Methods: Tumour lesions from 1058 endometrial cancer patients were immunohistochemically stained for MSH6, MSH2, PMS2 and MLH1. MMR protein expression was evaluated as loss or intact to determine MMR status, or by staining index to evaluate the prognostic potential of differential expression. Gene expression data from a local (n = 235) and the TCGA (n = 524) endometrial cancer cohorts was used for validation. Results: We identified a substantial agreement in MMR status between paired curettage and hysterectomy samples. Individual high expression of all four MMR markers associated with non-endometrioid subtype, and high MSH6 or MSH2 strongly associated with several aggressive disease characteristics including high tumour grade and FIGO stage, and for MSH6, with lymph node metastasis. In multivariate Cox analysis, MSH6 remained an independent prognostic marker, also within the endometrioid low-grade subgroup (P < 0.001). Conclusion: We demonstrate that in addition to determine MMR status, MMR protein expression levels, particularly MSH6, may add prognostic information in endometrial cancer.