Harmonisation of biobanking standards in endometrial cancer research

Background: Endometrial cancer is the most common gynaecological cancer and its incidence is predicted to escalate by 50–100% in 2025 with a parallel increase in associated mortality. Variations in the collection, processing and storage of biospecimens can affect the generalisability of the scientific data. We aimed to harmonise the collection of biospecimens, clinical data relevant to endometrial cancer and to develop standard operative procedures for the collection, processing and storage of endometrial cancer biospecimens. Methods: We designed research tools, which were evaluated and revised through three consensus rounds – to obtain local/regional, national and European consensus. Modified final tools were disseminated to a panel (n=40) representing all stakeholders in endometrial cancer research for consensus generation. Results: The final consensus demonstrated unanimous agreement with the minimal surgical and patient data collection tools. A high level of agreement was also observed for the other remaining standard tools. Conclusions: We here present the final versions of the tools, which are freely available and easily accessible to all endometrial cancer researchers. We believe that these tools will facilitate rapid progress in endometrial cancer research, both in future collaborations and in large-scale multicentre studies

The amount of preoperative endometrial tissue surface in relation to final endometrial cancer classification

Objective: To evaluate whether the amount of preoperative endometrial tissue surface is related to the degree of concordance with final low- and high-grade endometrial cancer (EC). In addition, to determine whether discordance is influenced by sampling method and impacts outcome. Methods: A retrospective cohort study within the European Network for Individualized Treatment of Endometrial Cancer (ENITEC). Surface of preoperative endometrial tissue samples was digitally calculated using ImageJ. Tumor samples were classified into low-grade (grade 1-2 endometrioid EC (EEC)) and high-grade (grade 3 EEC + non-endometroid EC). Results: The study cohort included 573 tumor samples. Overall concordance between pre- and postoperative diagnosis was 60.0%, and 88.8% when classified into low- and high-grade EC. Upgrading (preoperative low-grade, postoperative high-grade EC) was found in 7.8% and downgrading (preoperative high-grade, postoperative low-grade EC) in 26.7%. The median endometrial tissue surface was significantly lower in concordant diagnoses when compared to discordant diagnoses, respectively 18.7 mm2 and 23.5 mm2 (P = 0.022). Sampling method did not influence the concordance in tumor classification. Patients with preoperative high-grade and postoperative low-grade showed significant lower DSS compared to patients with concordant low-grade EC (P = 0.039). Conclusion: The amount of preoperative endometrial tissue surface was inversely related to the degree of concordance with final tumor low- and high-grade. Obtaining higher amount of preoperative endometrial tissue surface does not increase the concordance between pre- and postoperative low- and high-grade diagnosis in EC. Awareness of clinically relevant down- and upgrading is crucial to reduce subsequent over- or undertreatment with impact on outcome

Molecular profiling of circulating tumor cells links plasticity to the metastatic process in endometrial cancer

Background: About 20% of patients diagnosed with endometrial cancer (EC) are considered high-risk with unfavorable prognosis. In the framework of the European Network for Individualized Treatment in EC (ENITEC), we investigated the presence and phenotypic features of Circulating Tumor Cells (CTC) in high-risk EC patients. Methods: CTC isolation was carried out in peripheral blood samples from 34 patients, ranging from Grade 3 Stage IB to Stage IV carcinomas and recurrences, and 27 healthy controls using two methodologies. Samples were subjected to EpCAM-based immunoisolation using the CELLection™ Epithelial Enrich kit (Invitrogen, Dynal) followed by RTqPCR analysis. The phenotypic determinants of endometrial CTC in terms of pathogenesis, hormone receptor pathways, stem cell markers and epithelial to mesenchymal transition (EMT) drivers were asked. Kruskal-Wallis analysis followed by Dunn's post-test was used for comparisons between groups. Statistical significance was set at p < 0.05. Results: EpCAM-based immunoisolation positively detected CTC in high-risk endometrial cancer patients. CTC characterization indicated a remarkable plasticity phenotype defined by the expression of the EMT markers ETV5, NOTCH1, SNAI1, TGFB1, ZEB1 and ZEB2. In addition, the expression of ALDH and CD44 pointed to an association with stemness, while the expression of CTNNB1, STS, GDF15, RELA, RUNX1, BRAF and PIK3CA suggested potential therapeutic targets. We further recapitulated the EMT phenotype found in endometrial CTC through the up-regulation of ETV5 in an EC cell line, and validated in an animal model of systemic dissemination the propensity of these CTC in the accomplishment of metastasis. Conclusions: Our results associate the presence of CTC with high-risk EC. Gene-expression profiling characterized a CTC-plasticity phenotype with stemness and EMT features. We finally recapitulated this CTC-phenotype by over-expressing ETV5 in the EC cell line Hec1A and demonstrated an advantage in the promotion of metastasis in an in vivo mouse model of CTC dissemination and homing

Molecular profiling of circulating tumor cells links plasticity to the metastatic process in endometrial cancer

Background About 20% of patients diagnosed with endometrial cancer (EC) are considered high-risk with unfavorable prognosis. In the framework of the European Network for Individualized Treatment in EC (ENITEC), we investigated the presence and phenotypic features of Circulating Tumor Cells (CTC) in high-risk EC patients. Methods CTC isolation was carried out in peripheral blood samples from 34 patients, ranging from Grade 3 Stage IB to Stage IV carcinomas and recurrences, and 27 healthy controls using two methodologies. Samples were subjected to EpCAM-based immunoisolation using the CELLection™ Epithelial Enrich kit (Invitrogen, Dynal) followed by RTqPCR analysis. The phenotypic determinants of endometrial CTC in terms of pathogenesis, hormone receptor pathways, stem cell markers and epithelial to mesenchymal transition (EMT) drivers were asked. Kruskal-Wallis analysis followed by Dunn’s post-test was used for comparisons between groups. Statistical significance was set at p < 0.05. Results EpCAM-based immunoisolation positively detected CTC in high-risk endometrial cancer patients. CTC characterization indicated a remarkable plasticity phenotype defined by the expression of the EMT markers ETV5, NOTCH1, SNAI1, TGFB1, ZEB1 and ZEB2. In addition, the expression of ALDH and CD44 pointed to an association with stemness, while the expression of CTNNB1, STS, GDF15, RELA, RUNX1, BRAF and PIK3CA suggested potential therapeutic targets. We further recapitulated the EMT phenotype found in endometrial CTC through the up-regulation of ETV5 in an EC cell line, and validated in an animal model of systemic dissemination the propensity of these CTC in the accomplishment of metastasis. Conclusions Our results associate the presence of CTC with high-risk EC. Gene-expression profiling characterized a CTC-plasticity phenotype with stemness and EMT features. We finally recapitulated this CTC-phenotype by over-expressing ETV5 in the EC cell line Hec1A and demonstrated an advantage in the promotion of metastasis in an in vivo mouse model of CTC dissemination and homing

The amount of preoperative endometrial tissue surface in relation to final endometrial cancer classification

OBJECTIVETo evaluate whether the amount of preoperative endometrial tissue surface is related to the degree of concordance with final low- and high-grade endometrial cancer (EC). In addition, to determine whether discordance is influenced by sampling method and impacts outcome.METHODSA retrospective cohort study within the European Network for Individualized Treatment of Endometrial Cancer (ENITEC). Surface of preoperative endometrial tissue samples was digitally calculated using ImageJ. Tumor samples were classified into low-grade (grade 1-2 endometrioid EC (EEC)) and high-grade (grade 3 EEC + non-endometroid EC).RESULTSThe study cohort included 573 tumor samples. Overall concordance between pre- and postoperative diagnosis was 60.0%, and 88.8% when classified into low- and high-grade EC. Upgrading (preoperative low-grade, postoperative high-grade EC) was found in 7.8% and downgrading (preoperative high-grade, postoperative low-grade EC) in 26.7%. The median endometrial tissue surface was significantly lower in concordant diagnoses when compared to discordant diagnoses, respectively 18.7 mm2 and 23.5 mm2 (P = 0.022). Sampling method did not influence the concordance in tumor classification. Patients with preoperative high-grade and postoperative low-grade showed significant lower DSS compared to patients with concordant low-grade EC (P = 0.039).CONCLUSIONThe amount of preoperative endometrial tissue surface was inversely related to the degree of concordance with final tumor low- and high-grade. Obtaining higher amount of preoperative endometrial tissue surface does not increase the concordance between pre- and postoperative low- and high-grade diagnosis in EC. Awareness of clinically relevant down- and upgrading is crucial to reduce subsequent over- or undertreatment with impact on outcome.</p

Development of an Image-Guided Orthotopic Xenograft Mouse Model of Endometrial Cancer with Controllable Estrogen Exposure

Endometrial cancer (EC) is the most common gynaecological malignancy in Western society and the majority of cases are estrogen dependent. While endocrine drugs proved to be of insufficient therapeutic value in the past, recent clinical research shows promising results by using combinational regimens and pre-clinical studies and identified potential novel endocrine targets. Relevant pre-clinical models can accelerate research in this area. In the present study we describe an orthotopic and estrogen dependent xenograft mouse model of EC. Tumours were induced in one uterine horn of female athymic nude mice using the well-differentiated human endometrial adenocarcinoma Ishikawa cell line—modified to express the luciferase gene for bioluminescence imaging (BLI). BLI and contrast-enhanced computed-tomograph (CE-CT) were used to measure non-invasive tumour growth. Controlled estrogen exposure was achieved by the use of MedRod implants releasing 1.5 μg/d of 17β-estradiol (E2) in ovariectomized mice. Stable E2 serum concentration was demonstrated by LC-MS/MS. Induced tumours were E2 responsive as increased tumour growth was observed in the presence of E2 but not placebo, assessed by BLI, CE-CT, and tumour weight at sacrifice. Metastatic spread was assessed macroscopically by BLI and histology and was seen in the peritoneal cavity, in the lymphovascular space, and in the thoracic cavity. In conclusion, we developed an orthotopic xenograft mouse model of EC that exhibits the most relevant features of human disease, regarding metastatic spread and estrogen dependency. This model offers an easy to manipulate estrogen dosage (by simply adjusting the MedRod implant length), image-guided monitoring of tumour growth, and objectively measurable endpoints (including tumour weight). This is an excellent in vivo tool to further explore endocrine drug regimens and novel endocrine drug targets for EC

The cutoff for estrogen and progesterone receptor expression in endometrial cancer revisited: a european network for individualized treatment of endometrial cancer collaboration study

There is no consensus on the cutoff for positivity of estrogen receptor (ER) and progesterone receptor (PR) in endometrial cancer (EC). Therefore, we determined the cutoff value for ER and PR expression with the strongest prognostic impact on the outcome. Immunohistochemical expression of ER and PR was scored as a percentage of positive EC cell nuclei. Cutoff values were related to disease-specific survival (DSS) and disease-free survival (DFS) using sensitivity, specificity, and multivariable regression analysis. The results were validated in an independent cohort. The study cohort (n = 527) included 82% of grade 1-2 and 18% of grade 3 EC. Specificity for DSS and DFS was highest for the cutoff values of 1-30%. Sensitivity was highest for the cutoff values of 80-90%. ER and PR expression were independent markers for DSS at cutoff values of 10% and 80%. Consequently, three subgroups with distinct clinical outcomes were identified: 0-10% of ER/PR expression with, unfavorable outcome (5-year DSS = 75.9-83.3%); 20-80% of ER/PR expression with, intermediate outcome (5-year DSS = 93.0-93.9%); and 90-100% of ER/PR expression with, favorable outcome (5-year DSS = 97.8-100%). The association between ER/PR subgroups and outcomes was confirmed in the validation cohort (n = 265). We propose classification of ER and PR expression based on a high-risk (0-10%), intermediate-risk (20-80%), and low-risk (90-100%) group

Preoperative CA125 Significantly Improves Risk Stratification in High-Grade Endometrial Cancer

Patients with high-grade endometrial carcinoma (EC) have an increased risk of tumor spread and lymph node metastasis (LNM). Preoperative imaging and CA125 can be used in work-up. As data on cancer antigen 125 (CA125) in high-grade EC are limited, we aimed to study primarily the predictive value of CA125, and secondarily the contributive value of computed tomography (CT) for advanced stage and LNM. Patients with high-grade EC (n = 333) and available preoperative CA125 were included retrospectively. The association of CA125 and CT findings with LNM was analyzed by logistic regression. Elevated CA125 ((>35 U/mL), (35.2% (68/193)) was significantly associated with stage III-IV disease (60.3% (41/68)) compared with normal CA125 (20.8% (26/125), [p p p p < 0.001) independent of CA125. Stratification by CA125 resulted in an AUC of 0.484 (normal), and 0.660 (elevated). In multivariate analysis elevated CA125, non-endometrioid histology, pathological deep myometrial invasion ≥50%, and cervical involvement were significant predictors of LNM, whereas suspected LNM on CT was not. This shows that elevated CA125 is a relevant independent predictor of advanced stage and outcome specifically in high-grade EC

Immunohistochemical biomarkers are prognostic relevant in addition to the ESMO-ESGO-ESTRO risk classification in endometrial cancer

Objective: Pre-operative immunohistochemical (IHC) biomarkers are not incorporated in endometrial cancer (EC) risk classification. We aim to investigate the added prognostic relevance of IHC biomarkers to the ESMO-ESGO-ESTRO risk classification and lymph node (LN) status in EC. Methods: Retrospective multicenter study within the European Network for Individualized Treatment of Endometrial Cancer (ENITEC), analyzing pre-operative IHC expression of p53, L1 cell-adhesion molecule (L1CAM), estrogen receptor (ER) and progesterone receptor (PR), and relate to ESMO-ESGO-ESTRO risk groups, LN status and outcome. Results: A total of 763 EC patients were included with a median follow-up of 5.5-years. Abnormal IHC expression was present for p53 in 112 (14.7%), L1CAM in 79 (10.4%), ER- in 76 (10.0%), and PR- in 138 (18.1%) patients. Abnormal expression of p53/L1CAM/ER/PR was significantly related with higher risk classification groups, and combined associated with the worst outcome within the ‘high and advanced/metastatic’ risk group. In multivariate analysis p53-abn, ER/PR- and ESMO-ESGO-ESTRO ‘high and advanced/metastatic’ were independently associated with reduced disease-specific survival (DSS). Patients with abnormal IHC expression and lymph node metastasis (LNM) had the worst outcome. Patients with LNM and normal IHC expression had comparable outcome with patients without LNM and abnormal IHC expression. Conclusion: The use of pre-operative IHC biomarkers has important prognostic relevance in addition to the ESMO-ESGO-ESTRO risk classification and in addition to LN status. For daily clinical practice, p53/L1CAM/ER/PR expression could serve as indicator for surgical staging and refine selective adjuvant treatment by incorporation into the ESMO-ESGO-ESTRO risk classification

Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: a development and validation study

Background: Bayesian networks (BNs) are machine-learning-based computational models that visualize causal relationships and provide insight into the processes underlying disease progression, closely resembling clinical decision-making. Preoperative identification of patients at risk for lymph node metastasis (LNM) is challenging in endometrial cancer, and although several biomarkers are related to LNM, none of them are incorporated in clinical practice. The aim of this study was to develop and externally validate a preoperative BN to predict LNM and outcome in endometrial cancer patients. Methods and findings: Within the European Network for Individualized Treatment of Endometrial Cancer (ENITEC), we performed a retrospective multicenter cohort study including 763 patients, median age 65 years (interquartile range [IQR] 58-71), surgically treated for endometrial cancer between February 1995 and August 2013 at one of the 10 participating European hospitals. A BN was developed using score-based machine learning in addition to expert knowledge. Our main outcome measures were LNM and 5-year disease-specific survival (DSS). Preoperative clinical, histopathological, and molecular biomarkers were included in the network. External validation was performed using 2 prospective study cohorts: the Molecular Markers in Treatment in Endometrial Cancer (MoMaTEC) study cohort, including 446 Norwegian patients, median age 64 years (IQR 59-74), treated between May 2001 and 2010; and the PIpelle Prospective ENDOmetrial carcinoma (PIPENDO) study cohort, including 384 Dutch patients, median age 66 years (IQR 60-73), treated between September 2011 and December 2013. A BN called ENDORISK (preoperative risk stratification in endometrial cancer) was developed including the following predictors: preoperative tumor grade; immunohistochemical expression of estrogen receptor (ER), progesterone receptor (PR), p53, and L1 cell adhesion molecule (L1CAM); cancer antigen 125 serum level; thrombocyte count; imaging results on lymphadenopathy; and cervical cytology. In the MoMaTEC cohort, the area under the curve (AUC) was 0.82 (95% confidence interval [CI] 0.76-0.88) for LNM and 0.82 (95% CI 0.77-0.87) for 5-year DSS. In the PIPENDO cohort, the AUC for 5-year DSS was 0.84 (95% CI 0.78-0.90). The network was well-calibrated. In the MoMaTEC cohort, 249 patients (55.8%) were classified with <5% risk of LNM, with a false-negative rate of 1.6%. A limitation of the study is the use of imputation to correct for missing predictor variables in the development cohort and the retrospective study design. Conclusions: In this study, we illustrated how BNs can be used for individualizing clinical decision-making in oncology by incorporating easily accessible and multimodal biomarkers. The network shows the complex interactions underlying the carcinogenetic process of endometrial cancer by its graphical representation. A prospective feasibility study will be needed prior to implementation in the clinic