Molecular Classification of Endometrial Cancer and Its Impact on Therapy Selection.

Endometrial cancer (EC) accounts for 90% of uterine cancer cases. It is considered not only one of the most common gynecological malignancies but also one of the most frequent cancers among women overall. Nowadays, the differentiation of EC subtypes is based on immunohistochemistry and molecular techniques. It is considered that patients' prognosis and the implementation of the appropriate treatment depend on the cancer subtype. Patients with pathogenic variants in POLE have the most favorable outcome, while those with abnormal p53 protein have the poorest. Therefore, in patients with POLE mutation, the de-escalation of postoperative treatment may be considered, and patients with abnormal p53 protein should be subjected to intensive adjuvant therapy. Patients with a DNA mismatch repair (dMMR) deficiency are classified in the intermediate prognosis group as EC patients without a specific molecular profile. Immunotherapy has been recognized as an effective treatment method in patients with advanced or recurrent EC with a mismatch deficiency. Thus, different adjuvant therapy approaches, including targeted therapy and immunotherapy, are being proposed depending on the EC subtype, and international guidelines, such as those published by ESMO and ESGO/ESTRO/ESP, include recommendations for performing the molecular classification of all EC cases. The decision about adjuvant therapy selection has to be based not only on clinical data and histological type and stage of cancer, but, following international recommendations, has to include EC molecular subtyping. This review describes how molecular classification could support more optimal therapeutic management in endometrial cancer patients.

New staging of endometrial carcinoma - FIGO 2023.

AIM: To review the changes in the new version of the FIGO 2023 staging system for endometrial cancer. METHODS AND RESULTS: The new FIGO 2023 endometrial cancer staging system provides key updates for the diagnosis and treatment of endometrial cancer. An important step in diagnosis is molecular classification, which allows more accurate risk stratification for recurrence and the identification of targeted therapies. The new staging system, based on the recommendations of the international societies ESGO, ESTRO and ESP, incorporates not only the description of the pathological and anatomical extent of the disease, but also the histopathological characteristics of the tumour, including the histological type and the presence of lymphovascular space invasion. In addition, the staging system uses molecular testing to classify endometrial cancers into four prognostic groups: POLEmut, MMRd, NSMP and p53abn. Each group has its own specific characteristics and prognosis. The most significant changes have occurred in stages I and II, in which the sub-staging better reflects the biological behaviour of the tumour. This update increases the accuracy of prognosis and improves individualized treatment options for patients with endometrial cancer. CONCLUSION: The updated FIGO staging of endometrial cancer for 2023 incorporates different histologic types, tumour features, and molecular classifications to better reflect the current improved understanding of the complex nature of several endometrial cancer types and their underlying bio logic behaviour. The aim of the new endometrial cancer staging system is to better define stages with similar prognosis, allowing for more precise indication of individualised adjuvant radiation or systemic treatment, including the use of immunotherapy.

A new perspective on Endometrial Carcinoma classification and management strategies in context of molecular subtypes.

Endometrial cancer is the most common gynecological cancer and the second most prevalent female malignancy in the developed world. It is typically diagnosed in postmenopausal women, presenting with the characteristic clinical symptom of uterine abnormal bleeding. In the past, only two histological types were considered. However, it has become increasingly evident that endometrial cancer is a clinically heterogeneous disease, and this heterogeneity is closely associated with the diversity of underlying molecular alterations. The Cancer Genome Atlas classification has significantly advanced the diagnosis, risk stratification, and management of endometrial cancer by categorizing it into four molecular subgroups, each characterized by distinct mutational burdens and copy number alterations.

Prognostic value of molecular classification in stage IV endometrial cancer.

OBJECTIVES: Multiple studies have proven the prognostic value of molecular classification for stage I-III endometrial cancer patients. However, studies on the relevance of molecular classification for stage IV endometrial cancer patients are lacking. Hypothetically, poor prognostic molecular subtypes are more common in higher stages of endometrial cancer. Considering the poor prognosis of stage IV endometrial cancer patients, it is questionable whether molecular classification has additional prognostic value. Therefore, we determined which molecular subclasses are found in stage IV endometrial cancer and if there is a correlation with progression-free and overall survival. METHODS: A retrospective multicenter cohort study was conducted using data from five Dutch hospitals. Patients with stage IV endometrial cancer at diagnosis who were treated with primary cytoreductive surgery or cytoreductive surgery after induction chemotherapy between January 2000 and December 2018 were included. Exclusion criteria were age <18 years or recurrent disease. The molecular classification was performed centrally on all tumor samples according to the World Health Organization 2020 classification (including POLE and estrogen receptor status). The Kaplan-Meier method was used to calculate progression free and overall survival in the molecular subclasses, for the different histological subtypes and for estrogen receptor positive versus estrogen receptor negative tumors. Groups were compared using the log-rank test. RESULTS: 164 stage IV endometrial cancer patients were molecularly classified. Median age of the patients was 67 years (range 33-86). Most patients presented with a non-endometrioid histological subtype (58%). Intra-abdominal complete cytoreductive surgery was achieved in 60.4% of the patients. 101 tumors (61.6%) were classified as p53 abnormal, 35 (21.3%) as no specific molecular profile, 21 (12.8%) as mismatch repair deficient, and 6 (3%) as POLE mutated. Molecular classification had no significant impact on progression free (p=0.056) or overall survival (p=0.12) after cytoreductive surgery. Overall survival was affected by histologic subtype (p<0.0001) and estrogen receptor status (p=0.013). CONCLUSION: The distribution of the molecular subclasses in stage IV endometrial cancer patients differed substantially from the distribution in stage I-III endometrial cancer patients, with the unfavorable subclasses being more frequently present. Although the molecular classification was not prognostic in stage IV endometrial cancer, it could guide adjuvant treatment decisions.

Potential of molecular classification to guide fertility-sparing management among young patients with endometrial cancer.

The traditional histological classification system for endometrial carcinoma falls short in addressing the disease's molecular heterogeneity, prompting the need for alternative stratification methods. Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE) has emerged as a clinically efficient tool to categorize endometrial cancers according to mismatch repair deficiency, POLE exonuclease domain mutations, and p53 expression. However, the application of this classification to fertility-sparing treatments remains unexplored, and current guidelines lack specificity in how it should be used. In this review, we summarize the available literature and establish the framework for future investigations focused on molecular profiling-based risk assessment of endometrial cancer, with the goal of utilizing precision medicine to optimally counsel patients seeking fertility-sparing treatment. While the available evidence is limited and of low quality, it does provide insights and frames future perspectives for managing fertility-sparing approaches on the basis of molecular subtypes. Evidence suggests that mismatch repair-deficient tumors are likely to recur despite progestin therapy, emphasizing the need for alternative treatments, with targeted therapies being a new landscape that still needs to be explored. Tumors with POLE mutations exhibit a favorable prognosis, but the safety of hysteroscopic resection alone requires further investigation. p53 abnormal tumors have an unfavorable prognosis, raising questions about their suitability for fertility-sparing treatment. Lastly, the no specific molecular profile (or p53 wild-type) tumors, while having a relatively good prognosis, are heterogeneous and require more precise biomarkers to effectively guide therapy for those with poorer prognoses. Addressing these research gaps will lead to more precise guidelines to ensure optimal selection for fertility-sparing treatment.

Can miRNAs be useful biomarkers in improving prognostic stratification in endometrial cancer patients? An update review.

Endometrial cancer (EC) is the most common gynecological cancer, with annual incidence rates in Western countries ranging between 15 and 25 per 100 000 women. About 15% to 20% of patients with EC have high-risk disease and follow an aggressive clinical course. Unfortunately, the assessment of histologic parameters is poorly reproducible and conventional clinicopathological and molecular features do not reliably predict either the patient's response to the available treatments or the definition of personalized therapeutic approaches. In this context, the identification of novel diagnostic and prognostic biomarkers, which can be integrated in the current classification schemes, represents an unmet clinical need and an important challenge. miRNAs are key players in cancer by regulating the expression of specific target genes. Their role in EC, in association with clinical and prognostic tumor biomarkers, has been investigated but, so far, with little consensus among the studies. The present review aims to describe the recent advances in miRNAs research in EC taking into consideration the current classification schemes and to highlight the most promising miRNAs. Finally, a perspective point of view sheds light on the challenges ahead in the landscape of EC.

Fertility Sparing Treatments in Endometrial Cancer Patients: The Potential Role of the New Molecular Classification.

Endometrial cancer is the most frequent gynecological malignancy, and, although epidemiologically it mainly affects advanced age women, it can also affect young patients who want children and who have not yet completed their procreative project. Fertility sparing treatments are the subject of many studies and research in continuous evolution, and represent a light of hope for young cancer patients who find themselves having to face an oncological path before fulfilling their desire for motherhood. The advances in molecular biology and the more precise clinical and prognostic classification of endometrial cancer based on the 2013 The Cancer Genome Atlas classification allow for the selection of patients who can be submitted to fertility sparing treatments with increasing oncological safety. It would also be possible to predict the response to hormonal treatment by investigating the state of the genes of the mismatch repair.

Predicting endometrial cancer subtypes and molecular features from histopathology images using multi-resolution deep learning models.

The determination of endometrial carcinoma histological subtypes, molecular subtypes, and mutation status is critical for the diagnostic process, and directly affects patients' prognosis and treatment. Sequencing, albeit slower and more expensive, can provide additional information on molecular subtypes and mutations that can be used to better select treatments. Here, we implement a customized multi-resolution deep convolutional neural network, Panoptes, that predicts not only the histological subtypes but also the molecular subtypes and 18 common gene mutations based on digitized H&E-stained pathological images. The model achieves high accuracy and generalizes well on independent datasets. Our results suggest that Panoptes, with further refinement, has the potential for clinical application to help pathologists determine molecular subtypes and mutations of endometrial carcinoma without sequencing.

LG-ESSs and HG-ESSs: underlying molecular alterations and potential therapeutic strategies.

Endometrial stromal tumors (ESTs) include endometrial stromal nodule (ESN), low-grade endometrial stromal sarcoma (LG-ESS), high-grade endometrial stromal sarcoma (HG-ESS), and undifferentiated uterine sarcoma (UUS). Since these are rare tumor types, there is an unmet clinical need for the systematic therapy of advanced LG-ESS or HG-ESS. Cytogenetic and molecular advances in ESTs have shown that multiple recurrent gene fusions are present in a large proportion of LG-ESSs, and HG-ESSs are identified by the tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein epsilon (YWHAE)-family with sequence similarity 22 (FAM22) fusion. Recently, a group of ESSs harboring both zinc finger CCCH domain-containing protein 7B (ZC3H7B)-B-cell lymphoma 6 corepressor(BCOR) fusion and internal tandem duplication (ITD) of the BCOR gene have been provisionally classified as HG-ESSs. In this review, we firstly describe current knowledge about the molecular characteristics of recurrent aberrant proteins and their roles in the tumorigenesis of LG-ESSs and HG-ESSs. Next, we summarize the possibly shared signal pathways in the tumorigenesis of LG-ESSs and HG-ESSs, and list potentially actionable targets. Finally, based on the above discussion, we propose a few promising therapeutic strategies for LG-ESSs and HG-ESSs with recurrent gene alterations.

TCGA molecular subgroups of endometrial carcinoma in ovarian endometrioid carcinoma: A quantitative systematic review.

BACKGROUND: Ovarian endometrioid carcinoma (OEC) shares morphological and molecular features with endometrial endometrioid carcinoma (EEC). Several studies assessed the four TCGA groups of EEC, i.e. POLE-mutated (POLEmut), mismatch repair-deficient (MMRd), no specific molecular profile (NSMP) and p53-abnormal (p53abn), in OEC; however, it is unclear whether the TCGA groups have the same distribution and clinicopathological features between OEC and EEC. OBJECTIVE: To assess the distribution and clinicopathological features of the TCGA groups in OEC. METHODS: A systematic review and meta-analysis was carried out by searching 7 electronic databases from January 2013 to April 2021 for studies assessing the TCGA classification in OEC. Prevalence of each TCGA group in OEC and of FIGO grade 3 and stage>I was pooled using a random-effect model. Prevalence of TCGA groups was compared between OEC and EEC, extracting EEC data from a previous meta-analysis. Kaplan-Meier and Cox regression survival analyses were performed for progression-free survival (PFS). A significant p-value<0.05 was adopted. RESULTS: Four studies with 785 patients were included. The frequency of the TCGA groups in OEC vs EEC was: POLEmut = 5% vs 7.6% (p = 0.594); MMRd = 14.6% vs 29.2% (p < 0.001); p53abn = 14% vs 7.8% (p = 0.097); NSMP = 66.4% vs 55.4% (p = 0.002). The pooled prevalence of FIGO grade 3 was: POLEmut = 19.2%; MMRd = 18.3%; p53abn = 38.1%; NSMP = 14.5%. The pooled prevalence of FIGO stage >I was: POLEmut = 31.6%; MMRd = 42.8%; p53abn = 48.5%; NSMP = 24.6%. Two-, 5- and 10-year PFS was: POLEmut = 100%, 100%, and 100%; MMRd = 89.1%, 82.2% and 73.3%; p53abn = 61.7%, 50.2% and 39.6%; NSMP = 87.7%, 79.6% and 65.5%. The hazard ratio for disease progression (reference = NSMP) was: POLEmut = not estimable (no events); MMRd = 0.825 (p = 0.626); p53abn = 2.786 (p = 0.001). CONCLUSION: The prognostic value of the TCGA groups was similar between OEC and EEC, despite the differences in the frequency and pathological features of each group.

Comprehensive immunomolecular profiling of endometrial carcinoma: A tertiary retrospective study.

OBJECTIVE: Combined immunohistochemical and molecular classification using the Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE) independently predicts prognosis in endometrial carcinoma (EC). As next-generation sequencing (NGS) is entering clinical practice, we evaluated whether more comprehensive immunomolecular profiling (CIMP), including NGS and extended immunohistochemical analysis, could further refine the current ProMisE classification. METHODS: A series of 120 consecutive ECs, classified according to ProMisE, was stained immunohistochemically for CD3, CD8, PD-L1, beta-catenin and L1CAM. An in-house 96 gene NGS panel was performed on a subset of 44 ECs, representing the 4 ProMisE subgroups (DNA polymerase epsilon catalytic subunit exonuclease domain mutated (POLEmut), mismatch repair deficient (MMRd), p53 abnormal (p53 abn) and no specific molecular profile (NSMP) ECs). Cases harboring non-hotspot POLE variants were analyzed with Illumina TruSight Oncology 500 NGS panel (TSO500) as a surrogate for whole-exome sequencing. RESULTS: Eight cases harbored POLE variants, half of which were hotspots. Using TSO500, non-hotspot POLE variants were classified as pathogenic (3) or variant of unknown significance (1). POLEmut and MMRd ECs typically showed higher numbers of CD3+/CD8+ tumor-infiltrating lymphocytes and higher PD-L1 expression in tumor-infiltrating immune cells. p53 abn ECs showed significantly higher L1CAM immunoreactivity and frequently harbored gene amplifications including HER2 (25%), but typically lacked ARID1A or PTEN variants. Beta-catenin-positivity and FGFR2 variants were predominantly found in NSMP ECs. CONCLUSIONS: Our data show that CIMP adds significant value to EC characterization and may help to determine pathogenicity of non-hotspot POLE variants, encountered more frequently than expected in our series. In addition, CIMP may reveal ECs benefitting from immune checkpoint inhibition and allows upfront identification of targetable alterations, such as HER2 amplification in p53 abn ECs.

Impact of Molecular Classification on Treatment Paradigms in Uterine Cancers.

PURPOSE OF REVIEW: This article will discuss the recent data on the prognostic significance of molecular classification of endometrial carcinoma, as well as its impact on directing treatment decisions. RECENT FINDINGS: Molecular classification has emerged as a complement to the current paradigm of endometrial cancer (EC) risk stratification. POLE mutations appear to portend favorable prognoses, but data are insufficient to indicate withholding treatment based on this signature. Copy number high (CNH) EC carries a worse prognosis and may benefit from more aggressive therapy. MMRd tumors are likely to have other prognostic features that indicate adjuvant treatment and many recurrences respond favorably to pembrolizumab. Progression of molecular profiling may allow further discrimination of the no specific molecular profile (NSMP) group. Treatment for this group remains largely based on conventional risk factors. For both the NSMP and the CNH groups, treatment with lenvatinib and pembrolizumab is an attractive contemporary option for recurrence management. Molecular classification is a useful adjunct to conventional risk stratification paradigms for both prognostic counseling and treatment selection. Clinical trials incorporating molecular signatures in assigning treatment strategies may further elucidate the value of this classification system.

Performance of a HER2 testing algorithm specific for p53-abnormal endometrial cancer.

AIMS: Human epidermal growth factor receptor 2 (HER2) amplification in endometrial cancer (EC) is almost completely confined to the p53-abnormal (p53abn) molecular subtype and independent of histological subtype. HER2 testing should therefore be molecular subtype-directed. However, the most optimal approach for HER2 testing in EC has not been fully established. Therefore, we developed an EC-specific HER2 immunohistochemistry (IHC) scoring method and evaluated its reproducibility and performance to establish an optimal diagnostic HER2 testing algorithm for p53abn EC. METHODS AND RESULTS: HER2 IHC slides of 78 p53abn EC were scored by six gynaecopathologists according to predefined EC-specific IHC scoring criteria. Interobserver agreement was calculated using Fleiss' kappa and the first-order agreement coefficient (AC1). The consensus IHC score was compared with HER2 dual in-situ hybridisation (DISH) results. Sensitivity and specificity were calculated. A substantial interobserver agreement was found using three- or two-tiered scoring [κ = 0.675, 95% confidence interval (CI) = 0.633-0.717; AC1 = 0.723, 95% CI = 0.643-0.804 and κ = 0.771, 95% CI = 0.714-0.828; AC1 = 0.774, 95% CI = 0.684-0.865, respectively]. Sensitivity and specificity for the identification of HER2-positive EC was 100 and 97%, respectively, using a HER2 testing algorithm that recommends DISH in all cases with moderate membranous staining in >10% of the tumour (IHC+). Performing DISH on all IHC-2+ and -3+ cases yields a sensitivity and specificity of 100%. CONCLUSIONS: Our EC-specific HER2 IHC scoring method is reproducible. A screening strategy based on IHC scoring on all cases with subsequent DISH testing on IHC-2+/-3+ cases has perfect test accuracy for identifying HER2-positive EC.

Clinical features of ProMisE groups identify different phenotypes of patients with endometrial cancer.

BACKGROUND: The Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE) groups has identified four molecular prognostic groups of endometrial cancer (EC): POLE-mutated (POLE-mt), mismatch repair-deficient (MMR-d), p53-abnormal (p53-abn), p53-wild-type (p53-wt). These groups might have different pathogenesis and risk factors, and might occur in different phenotypes of patients. However, these data are still lacking. OBJECTIVE: To provide a clinical characterization of the ProMisE groups of EC. METHODS: A systematic review and meta-analysis was performed by searching seven electronic databases from their inception to December 2020, for all studies reporting clinical characteristics of EC patients in each ProMisE group. Pooled means of age and BMI and pooled prevalence of FIGO stage I and adjuvant treatment in each ProMisE group were calculated. RESULTS: Six studies with 1, 879 women were included in the systematic review. Pooled means (with standard error) and prevalence values were: in the MMR-d group, age = 66.5 ± 0.6; BMI = 30.6 ± 1.2; stage I = 72.6%; adjuvant treatment = 47.3%; in the POLE-mt group, age = 58.6 ± 2.7; BMI = 27.2 ± 0.9; stage I = 93.7%; adjuvant treatment = 53.6%; in the p53-wt group, age = 64.2 ± 1.9; BMI = 32.3 ± 1.4; stage I = 80.5%; adjuvant treatment = 45.3%; in the p53-abn group, age = 71.1 ± 0.5; BMI = 29.1 ± 0.5; stage I = 50.8%; adjuvant treatment = 64.4%. CONCLUSION: The ProMisE groups identify different phenotypes of patients. The POLE-mt group included the youngest women, with the lower BMI and the highest prevalence of stage I. The p53-wt group included patients with the highest BMI. The p53-abn group included the oldest women, with the highest prevalence of adjuvant treatment and the lowest prevalence of stage I. The MMR-d group showed intermediate values among the ProMisE groups for all clinical features.

p53abn Endometrial Cancer: understanding the most aggressive endometrial cancers in the era of molecular classification.

Over the past decade, our understanding of endometrial cancer has changed dramatically from the two-tiered clinicopathologic classification system of type I and type II endometrial cancer through to the four distinct molecular subtypes identified by The Cancer Genome Atlas (TCGA) in 2013. In both systems there is a small subset of endometrial cancers (serous histotype/high numbers of somatic copy number abnormalities) that account for a disproportionately high percentage of endometrial cancer related deaths. This subset can be identified in routine clinical practice by first identifying the approximately one-third of endometrial cancers that are either ultramutated/POLEmut tumors, with pathogenic mutations in the exonuclease domain of POLE, or hypermutated/MMRd tumors, with loss of DNA mismatch repair. Immunostaining for p53 stratifies the remaining endometrial cancers into those with wild-type staining pattern and those with mutant pattern staining (p53abn endometrial cancer). This latter group of p53abn endometrial cancer is the subject of this review. Most p53abn endometrial cancers are serous type and high grade, but it also includes other histotypes and lower grade tumors, and has consistently been associated with the poorest clinical outcomes. Although it only accounts for 15% of all endometrial cancer cases, it is responsible for 50-70% of endometrial cancer mortality. A better understanding of the molecular alterations in the p53abn subgroup, beyond the ubiquitous and definitional TP53 mutations, is required so we can identify better treatments for these most aggressive endometrial cancers. Recent evidence has shown improved survival outcomes with the addition of chemotherapy compared with radiation alone in p53abn endometrial cancers. Opportunities for targeted therapy for p53abn endometrial cancers also exist with a proportion of p53abn endometrial cancers known to have homologous recombination deficiency (HRD) or human epidermal growth factor 2 (HER2) overexpression/amplification. This review will provide an overview of our current understanding of p53abn endometrial cancer.

Construction of a nine DNA repair-related gene prognostic classifier to predict prognosis in patients with endometrial carcinoma.

BACKGROUND: Endometrial cancer (EC) is one of the most common gynecological malignancies worldwide. However, the molecular mechanisms and the prognostic prediction for EC patients remain unclear. METHODS: In the current study, we performed an in-depth analysis of over 500 patients which were obtained from the Cancer Genome Atlas (TCGA) database. The bioinformatics analysis included gene set enrichment analysis (GSEA) and Cox and lasso regression analyses to ensure overall survival (OS)-related genes, moreover, to construct a prognostic model and a nomogram for EC patients. RESULTS: GSEA identified 4 gene sets significantly associated with EC, which are DNA repair, unfolded protein response, reactive oxygen species pathway and UV response up. Twenty-five OS-related DNA repair genes were screened out, after that, a 9-mRNA signature was constructed to measure the risk scores of patients with different outcomes. In addition, a nomogram contained the 9-mRNA model and clinical parameters was also presented to assess the prognosis. Patients with low risk were more likely to have sensitivity to paclitaxel, vinblastine, rapamycin, metformin, imatinib, Akt inhibitor and lapatinib. CONCLUSIONS: The identified highly enriched gene sets may offer a novel insight into the tumorigenesis and treatment of EC. Additionally, the constructed 9-mRNA model and the nomogram have prominent clinical implications for prognosis evaluation and specific therapy guidance for EC patients.

Combination of Proactive Molecular Risk Classifier for Endometrial cancer (ProMisE) with sonographic and demographic characteristics in preoperative prediction of recurrence or progression of endometrial cancer.

OBJECTIVE: To evaluate the ability of demographic and sonographic variables and the Proactive Molecular Risk Classifier for Endometrial cancer (ProMisE) classification to predict preoperatively tumor recurrence or progression in women with endometrial cancer. METHODS: The study included 339 women with histologically confirmed endometrial cancer who underwent expert transvaginal ultrasound in a single center before surgery as part of the prospective International Endometrial Tumor Analysis 4 study or who were evaluated using the same protocol. The tumors were classified according to histotype, FIGO (International Federation of Gynecology and Obstetrics) grade and FIGO stage. In addition, molecular analysis was performed for classification into the four ProMisE subtypes: polymerase-ϵ exonuclease domain mutations (POLE EDM), mismatch repair proteins deficiency (MMR-D), protein 53 wild type (p53 wt) and protein 53 abnormal (p53 abn). Demographic and preoperative sonographic characteristics, tumor recurrence or progression and survival were compared between the ProMisE subgroups. Cox regression analysis was used to identify prognostic factors associated with recurrence or progression, using univariable models to study crude associations and multivariable models to study adjusted associations. Logistic regression and receiver-operating-characteristics (ROC)-curve analysis were used to assess the predictive ability of the preoperative prognostic factors regarding recurrence or progression of cancer within 3 years after surgery, and to compare their predictive ability to that of the European Society for Medical Oncology (ESMO) preoperative (based on depth of myometrial invasion, histotype and grade) and postoperative (based on histotype, grade, surgical stage and lymphovascular space invasion) risk classifications. In a separate subanalysis, cases were stratified according to ProMisE p53 abn status (present vs absent) and sonographic tumor size (anteroposterior (AP) diameter < 2 cm vs ≥ 2 cm). RESULTS: Median follow-up time from surgery was 58 months (interquartile range, 48-71 months; range, 0-102 months). Recurrence or progression of cancer occurred in 51/339 (15%) women, comprising 14% of those with MMR-D, 8% of those with POLE EDM, 9% of those with p53 wt and 45% of those with p53 abn ProMisE subtype. On multivariable analysis, age, waist circumference, ProMisE subtype and tumor extension and AP diameter on ultrasound were associated with tumor recurrence or progression. A multivariable model comprising ProMisE subtype, age, waist circumference and sonographic tumor extension and size (area under the ROC curve (AUC), 0.89 (95% CI, 0.85-0.93)) had comparable ability to predict tumor recurrence/progression to that of a multivariable model comprising histotype, grade, age, waist circumference and sonographic tumor extension and size (AUC, 0.88 (95% CI, 0.83-0.92)), and better predictive ability than both the preoperative (AUC, 0.74 (95% CI, 0.67-0.82); P < 0.01) and postoperative (AUC, 0.79 (95% CI, 0.72-0.86); P < 0.01) ESMO risk classifications. Women with a combination of non-p53 abn subtype and tumor size < 2 cm (164/339 (48%)) had a very low risk (1.8%) of tumor recurrence or progression. CONCLUSIONS: The combination of demographic characteristics, sonographic findings and ProMisE subtype had better preoperative predictive ability for tumor recurrence or progression than did the ESMO classification, supporting their use in the preoperative risk stratification of women with endometrial cancer. The combination of p53 status with ultrasound tumor size has the potential to identify preoperatively a large group of women with a very low risk of recurrence or progression. © 2020 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology. - Legal Statement: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.