IMPORTANCE: Patients with low-grade (ie, grade 1-2) endometrial cancer (EC) are characterized by their favorable prognosis compared with patients with high-grade (ie, grade 3) EC. With the implementation of molecular profiling, the prognostic relevance of tumor grading might lose attention. As most patients present with low-grade EC and have an excellent outcome, the value of molecular profiling for these patients is unclear. OBJECTIVE: To determine the association of molecular profiling with outcomes among patients with low-grade EC. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study included a multicenter international European cohort of patients diagnosed with EC between 1994 and 2018, with a median follow-up of 5.9 years. Molecular subgroups were determined by next-generation sequencing using single-molecule molecular inversion probes and by immunohistochemistry. Subsequently, tumors were classified as polymerase epsilon (POLE)-altered, microsatellite instable (MSI), tumor protein p53 (TP53)-altered, or no specific molecular profile (NSMP). Patients diagnosed with any histological subtypes and FIGO (International Federation of Gynecology and Obstetrics) stages of EC were included, but patients with early-stage EC (FIGO I-II) were only included if they had known lymph node status. Data were analyzed February 20 to June 16, 2022. EXPOSURES: Molecular testing of the 4 molecular subgroups. MAIN OUTCOMES AND MEASURES: The main outcome was disease-specific survival (DSS) within the molecular subgroups. RESULTS: A total of 393 patients with EC were included, with a median (range) age of 64.0 (31.0-86.0) years and median (range) body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) of 29.1 (18.0-58.3). Most patients presented with early-stage (290 patients [73.8%]) and low-grade (209 patients [53.2%]) disease. Of all patients, 33 (8.4%) had POLE-altered EC, 78 (19.8%) had MSI EC, 72 (18.3%) had TP53-altered EC, and 210 (53.4%) had NSMP EC. Across all molecular subgroups, patients with low-grade EC had superior 5-year DSS compared with those with high-grade EC, varying between 90% to 100% vs 41% to 90% (P < .001). Multivariable analysis in the entire cohort including age, tumor grade, FIGO stage, lymphovascular space invasion, and the molecular subgroups as covariates found that only high-grade (hazard ratio [HR], 4.29; 95% CI, 2.15-8.53; P < .001), TP53-altered (HR, 1.76; 95% CI, 1.04-2.95; P = .03), and FIGO stage III or IV (HR, 4.26; 95% CI, 2.50-7.26; P < .001) disease were independently associated with reduced DSS. CONCLUSIONS AND RELEVANCE: This cohort study found that patients with low-grade EC had an excellent prognosis independent of molecular subgroup. These findings do not support routine molecular profiling in patients with low-grade EC, and they demonstrate the importance of primary diagnostic tumor grading and selective profiling in low-grade EC to increase cost-effectiveness.

• MeSH
• endometroidní karcinom * patologie   MeSH
• kohortové studie MeSH
• lidé středního věku MeSH
• lidé MeSH
• nádory endometria * MeSH
• prognóza MeSH
• retrospektivní studie MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• multicentrická studie MeSH

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.

• MeSH
• Bayesova věta MeSH
• hodnocení rizik MeSH
• lidé středního věku MeSH
• lidé MeSH
• lymfatické metastázy MeSH
• nádorové biomarkery metabolismus   MeSH
• nádory endometria patologie   MeSH
• prospektivní studie MeSH
• receptory pro estrogeny metabolismus   MeSH
• receptory progesteronu MeSH
• retrospektivní studie MeSH
• senioři MeSH
• stupeň nádoru MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• multicentrická studie MeSH
• práce podpořená grantem MeSH

Discrimination between low- and high-grade endometrial carcinomas (ECs) is clinically relevant but can be challenging for pathologists, with moderate interobserver agreement. Insulin-like growth factor-II mRNA-binding protein 3 (IMP3) is an oncofoetal protein that is associated with nonendometrioid endometrial carcinomas but has been limited studied in endometrioid carcinomas. The aim of this study is to investigate the diagnostic and prognostic value of IMP3 in the discrimination between low- and high-grade ECs and its added value to L1CAM. IMP3 and L1CAM expression was assessed in tumors from 378 patients treated for EC at 1 of 9 participating European Network for Individualised Treatment of Endometrial Cancer centers. IMP3 was expressed in 24.6% of the tumors. In general, IMP3 was more homogeneously expressed than L1CAM. IMP3 expression was significantly associated with advanced stage, nonendometrioid histology, grade 3 tumors, deep myometrial invasion, lymphovascular space invasion, distant recurrences, overall mortality, and disease-related mortality. Simultaneous absence of IMP3 and L1CAM expression showed the highest accuracy for identifying low-grade carcinomas (area under the curve 0.766), whereas simultaneous expression of IMP3 and L1CAM was strongly associated with high-grade carcinomas (odds ratio 19.7; 95% confidence interval 9.2-42.2). Even within endometrioid carcinomas, this combination remained superior to IMP3 and L1CAM alone (odds ratio 8.6; 95% confidence interval 3.4-21.9). In conclusion, IMP3 has good diagnostic value and together with L1CAM represents the optimal combination of diagnostic markers for discrimination between low- and high-grade ECs compared to IMP3 and L1CAM alone. Because of the homogenous expression of IMP3, this marker might be valuable in preoperative biopsies when compared to the more patchy L1CAM expression.

• MeSH
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• molekula buněčné adheze nervové L1 analýza   biosyntéza   MeSH
• nádorové biomarkery analýza   MeSH
• nádory endometria patologie   MeSH
• proteiny vázající RNA analýza   biosyntéza   MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• senzitivita a specificita MeSH
• stupeň nádoru metody   MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• multicentrická studie MeSH