High concordance of molecular tumor alterations between pre-operative curettage and hysterectomy specimens in patients with endometrial carcinoma

A Novel Approach to Preoperative Risk Stratification in Endometrial Cancer: The Added Value of Immunohistochemical Markers

Background: The current model used to preoperatively stratify endometrial cancer (EC) patients into low- and high-risk groups is based on histotype, grade, and imaging method and is not optimal. Our study aims to prove whether a new model incorporating immunohistochemical markers, L1CAM, ER, PR, p53, obtained from preoperative biopsy could help refine stratification and thus the choice of adequate surgical extent and appropriate adjuvant treatment.

Materials and Methods: The following data were prospectively collected from patients operated for EC from January 2016 through August 2018: age, pre- and post-operative histology, grade, lymphovascular space invasion, L1CAM, ER, PR, p53, imaging parameters obtained from ultrasound, CT chest/abdomen, final FIGO stage, and current decision model (based on histology, grade, imaging method).

Results: In total, 132 patients were enrolled. The current model revealed 48% sensitivity and 89% specificity for high-risk group determination. In myometrial invasion >50%, lower levels of ER (p = 0.024), PR (0.048), and higher levels of L1CAM (p = 0.001) were observed; in cervical involvement a higher expression of L1CAM (p = 0.001), lower PR (p = 0.014); in tumors with positive LVSI, higher L1CAM (p = 0.014); in cases with positive LN, lower expression of ER/PR (p < 0.001), higher L1CAM (p = 0.002) and frequent mutation of p53 (p = 0.008).

Cut-offs for determination of high-risk tumors were established: ER <78% (p = 0.001), PR <88% (p = 0.008), and L1CAM ≥4% (p < 0.001). The positive predictive values (PPV) for ER, PR, and L1CAM were 87% (60.8–96.5%), 63% (52.1–72.8%), 83% (70.5–90.8%); the negative predictive values (NPV) for each marker were as follows: 59% (54.5–63.4%), 65% (55.6–74.0%), and 77% (67.3–84.2%). Mutation of p53 revealed PPV 94% (67.4–99.1%) and NPV 61% (56.1–66.3%). When immunohistochemical markers were included into the current diagnostic model, sensitivity improved (48.4 vs. 75.8%, p < 0.001). PPV was similar for both methods, while NPV (i.e., the probability of extremely low risk in negative test cases) was improved (66 vs. 78.9%, p < 0.001).

Conclusion: We proved superiority of new proposed model using immunohistochemical markers over standard clinical practice and that new proposed model increases accuracy of prognosis prediction. We propose wider implementation and validation of the proposed model.

A Prediction Model for Preoperative Risk Assessment in Endometrial Cancer Utilizing Clinical and Molecular Variables

The utility of comprehensive surgical staging in patients with low risk disease has been questioned. Thus, a reliable means of determining risk would be quite useful. The aim of our study was to create the best performing prediction model to classify endometrioid endometrial cancer (EEC) patients into low or high risk using a combination of molecular and clinical-pathological variables. We then validated these models with publicly available datasets. Analyses between low and high risk EEC were performed using clinical and pathological data, gene and miRNA expression data, gene copy number variation and somatic mutation data. Variables were selected to be included in the prediction model of risk using cross-validation analysis; prediction models were then constructed using these variables. Model performance was assessed by area under the curve (AUC). Prediction models were validated using appropriate datasets in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A prediction model with only clinical variables performed at 88%. Integrating clinical and molecular data improved prediction performance up to 97%. The best prediction models included clinical, miRNA expression and/or somatic mutation data, and stratified pre-operative risk in EEC patients. Integrating molecular and clinical data improved the performance of prediction models to over 95%, resulting in potentially useful clinical tests.

Clinicopathological and survival analysis of uterine papillary serous carcinoma: a single institutional review of 106 cases

Objectives

The objectives of this study were to analyze clinicopathological features and to investigate the prognostic determinants in patients with uterine papillary serous carcinoma (UPSC).

Materials and methods

A cohort of 106 UPSC patients diagnosed and treated at Peking Union Medical College Hospital between 2000 and 2016 were retrospectively reviewed. The Kaplan-Meier method and Cox regression analysis were used for survival analysis. Differences between categorical data were calculated by using the chi-squared test.

Results

The median follow-up was 29.0 months (range =2-170 months), with an overall recurrence rate of 35.8%. The coincidence rate between preoperative endometrial sampling and postoperative definitive pathology of hysteroscopy group was significantly higher than that of the dilation and curettage group (88.5% vs 65.0%, P=0.019). Adjuvant therapy-treated patients with stage I UPSC experienced significantly fewer recurrences than those receiving observation (P=0.003). Patients with advanced-stage UPSC who received combination therapy demonstrated a lower risk of local recurrence compared with those who received chemotherapy alone with a borderline significance (P=0.051). Elevated serum cancer antigen 125 level was associated with advanced-stage disease and recurrence (P<0.001). In multivariate analysis, tumor stage and optimal cytoreduction were independent predictors of survival. In substage analysis, complete surgical staging was associated with better overall survival (OS; yes vs no, HR: 0.05 [95% CI: 0.01-0.51], P=0.037) in patients with stage I UPSC. As for advanced stage, paclitaxel-platinum chemotherapy regimen and optimal cytoreduction were independent favorable prognostic factors for progression-free survival (paclitaxel-carboplatin [TC] vs other; HR =0.38, P=0.010; yes vs no, HR =0.45, P=0.032) and OS (TC vs other, HR =0.38, P=0.022; yes vs no, HR =0.54, P=0.013).

Conclusion

In patients with stage I UPSC, complete staging was associated with better OS, and therefore, it should be performed in all patients. Tumor stage and optimal cytoreduction are the most significant prognostic factors. Recurrence can be improved in stage I patients treated with adjuvant therapy and in patients with advanced-stage disease treated with combined therapy. TC regimen may be the preferred regimen for chemotherapy.

Tumor Grade Correlation Between Preoperative Biopsy and Final Surgical Specimen in Endometrial Cancer: The Use of Different Diagnostic Methods and Analysis of Associated Factors

Objective

This study aimed to identify the correlation between histology tumor grade of the preoperative biopsy using dilatation and curettage (D&C), Pipelle, or hysteroscopy and final surgical specimen in women with endometrioid endometrial cancer.

Materials and Methods

Patients on whom a preoperative biopsy was performed between 2009 and 2016 were reviewed and cases with apparent early-stage endometrioid endometrial cancer were included in the study. The accuracy of preoperative biopsy performed before hysterectomy using D&C, Pipelle, or hysteroscopy was compared.

Results

A total of 332 patients were included. The diagnostic method was D&C in 43 cases (13%), Pipelle in 102 (31%), and hysteroscopy in 187 (56%). The preoperative diagnosis included G1 tumors in 177 cases (53.3%), G2 in 103 (31%), and G3 in 52 (15.6%). The surgical specimen confirmed endometrioid endometrial tumor in 309 patients (93%).

The accuracy rates of preoperative biopsy and surgical specimen were 74.69%, 73.19%, and 89.75% for G1, G2, and G3, respectively. Hysteroscopy showed better κ index (κ = 0.551) than did D&C (κ = 0.392) and Pipelle (κ = 0.430). Tumor diameter greater than 30 mm was the only factor independently associated with absence of correlation between preoperative and postoperative tumor grade (odds ratio [95% confidence interval], 1.959 [1.096–3.504], P = 0.023).

Conclusions

Preoperative biopsy, regardless of the method, has its limitations in predicting the tumor grade compared with final surgical specimen in women with endometrioid endometrial cancer at an apparent early stage. Concordance between the biopsy and hysterectomy specimen is less likely to happen in the case of preoperative G1 or G2 tumors, as well as in big tumors. Although hysteroscopy was associated with the highest tumor grade agreement, no differences in correlation between the 3 methods (D&C, Pipelle, and hysteroscopy) were found.

Asparaginase-like protein 1 expression in curettage independently predicts lymph node metastasis in endometrial carcinoma: a multicentre study

OBJECTIVE

Correct preoperative identification of high-risk patients is important to optimise surgical treatment and improve survival. We wanted to explore if asparaginase-like protein 1 (ASRGL1) expression in curettage could predict lymph node metastases and poor outcome, potentially improving preoperative risk stratification.

DESIGN

Multicentre study.

SETTING

Ten hospitals in Norway, Sweden and Belgium.

POPULATION

Women diagnosed with endometrial carcinoma.

METHODS

ASRGL1 expression in curettage specimens from 1144 women was determined by immunohistochemistry.

MAIN OUTCOME MEASURES

ASRGL1 status related to disease-specific survival, lymph node status, preoperative imaging parameters and clinicopathological data.

RESULTS

ASRGL1 expression had independent prognostic value in multivariate survival analyses, both in the whole patient population (hazard ratio (HR) 1.63, 95% CI 1.11-2.37, P = 0.012) and in the low-risk curettage histology subgroup (HR 2.54, 95% CI 1.44-4.47, P = 0.001). Lymph node metastases were more frequent in women with low expression of ASRGL1 compared with women with high ASRGL1 levels (23% versus 10%, P < 0.001), and low ASRGL1 level was found to independently predict lymph node metastases (odds ratio 2.07, 95% CI 1.27-3.38, P = 0.003).

CONCLUSIONS

Low expression of ASRGL1 in curettage independently predicts lymph node metastases and poor disease-specific survival.

TWEETABLE ABSTRACT

Low ASRGL1 expression in curettage predicts lymph node metastasis and poor survival in endometrial carcinoma.

Molecular-integrated risk profile to determine adjuvant radiotherapy in endometrial cancer: Evaluation of the pilot phase of the PORTEC-4a trial

OBJECTIVE

The Post-Operative Radiation Therapy in Endometrial Carcinoma (PORTEC)-4a trial is a randomized trial for women with high-intermediate risk endometrial cancer (EC), comparing individualized adjuvant treatment based on a molecular-integrated risk profile to standard adjuvant treatment; vaginal brachytherapy. To evaluate patient acceptability and pathology logistics of determining the risk profile, a pilot phase was included in the study.

METHODS

PORTEC-4a is ongoing and the first 50 patients enrolled were included in the pilot phase. Primary endpoints of the pilot phase were patient acceptance, evaluated by analyzing the screening logs of the participating centers, and logistical feasibility of determination of the risk profile within 2 weeks, evaluated by analyzing the pathology database.

RESULTS

In the first year, 145 eligible women were informed about the trial at 13 centers, of whom 50 (35%) provided informed consent. Patient accrual ranged from 0 to 57% per center. Most common reasons for not participating were: not willing to participate in any trial (43.2%) and not willing to risk receiving no adjuvant treatment (32.6%). Analysis of the pathology database showed an average time between randomization and determination of the molecular-integrated risk profile of 10.2 days (1-23 days). In 5 of the 32 patients (15.6%), pathology review took >2 weeks.

CONCLUSIONS

The PORTEC-4a trial design was proven feasible with a satisfactory patient acceptance rate and an optimized workflow of the determination of the molecular-integrated risk profile. PORTEC-4a is the first randomized trial to investigate use of a molecular-integrated risk profile to determine adjuvant treatment in EC.

Limited impact of intratumour heterogeneity on molecular risk assignment in endometrial cancer

Introduction

Individual prediction of tumour behaviour based on molecular markers may refine adjuvant treatment strategies in endometrial cancer (EC). As these molecular alterations are determined in a small tumour fraction, high intratumour heterogeneity may interfere with correct risk prediction. This study aimed to investigate to which extent intratumour heterogeneity exists for molecular markers and whether it affects the molecular risk assignment in EC.

Methods

Forty-nine ECs (three tumour blocks/case) were selected with alterations in POLE (n=10), CTNNB1 (n=8), p53 (n=10), mismatch repair (n=11), L1CAM (n=10), and ECs without any of these markers (n=9). Nine ECs carried more than one molecular marker. All 147 blocks were analysed for POLE exonuclease domain and CTNNB1 exon 3 mutations, and for p53, mismatch repair and L1CAM protein expression. All blocks were assigned to a favourable, intermediate or unfavourable risk group, based on a molecular risk assignment.

RESULTS

Concordance between the three tumour blocks for POLE and CTNNB1 mutational status, and p53, mismatch repair and L1CAM protein expression was found in 100% (48/48), 95.9% (47/49), 93.9% (46/49), 98.0% (48/49), and 91.8% (45/49) of tumours, respectively. These discordances were found in a total of nine cases (18.4%). The intratumour heterogeneity impacted the risk assignment in five cases (10.2%).

Conclusion

Intratumour heterogeneity of prognostic molecular markers in EC without morphologic heterogeneity is uncommon among three tumour fractions, affecting the molecular risk allocation in a limited number of cases. This low intratumour heterogeneity facilitates the implementation of the molecular risk assignment, advocating its use in clinical decision making.

Genetic analysis of uterine aspirates improves the diagnostic value and captures the intra-tumor heterogeneity of endometrial cancers

Endometrial cancer is the most common cancer of the female genital tract in developed countries. Although the majority of endometrial cancers are diagnosed at early stages and the 5-year overall survival is around 80%, early detection of these tumors is crucial to improve the survival of patients given that the advanced tumors are associated with a poor outcome. Furthermore, correct assessment of the pre-clinical diagnosis is decisive to guide the surgical treatment and management of the patient. In this sense, the potential of targeted genetic sequencing of uterine aspirates has been assessed as a pre-operative tool to obtain reliable information regarding the mutational profile of a given tumor, even in samples that are not histologically classifiable. A total of 83 paired samples were sequenced (uterine aspirates and hysterectomy specimens), including 62 endometrioid and non-endometrioid tumors, 10 cases of atypical hyperplasia and 11 non-cancerous endometrial disorders. Even though diagnosing endometrial cancer based exclusively on genetic alterations is currently unfeasible, mutations were mainly found in uterine aspirates from malignant disorders, suggesting its potential in the near future for supporting the standard histologic diagnosis. Moreover, this approach provides the first evidence of the high intra-tumor genetic heterogeneity associated with endometrial cancer, evident when multiple regions of tumors are analyzed from an individual hysterectomy. Notably, the genetic analysis of uterine aspirates captures this heterogeneity, solving the potential problem of incomplete genetic characterization when a single tumor biopsy is analyzed.

New classification of endometrial cancers: the development and potential applications of genomic-based classification in research and clinical care

Endometrial carcinoma (EC) is the fourth most common cancer in women in the developed world. Classification of ECs by histomorphologic criteria has limited reproducibility and better tools are needed to distinguish these tumors and enable a subtype-specific approach to research and clinical care. Based on the Cancer Genome Atlas, two research teams have developed pragmatic molecular classifiers that identify four prognostically distinct molecular subgroups. These methods can be applied to diagnostic specimens (e.g., endometrial biopsy) with the potential to completely change the current risk stratification systems and enable earlier informed decision making. The evolution of genomic classification in ECs is shared herein, as well as potential applications and discussion of the essential research still needed in order to optimally integrate molecular classification in to current standard of care.

Molecular classification of endometrial carcinoma on diagnostic specimens is highly concordant with final hysterectomy: Earlier prognostic information to guide treatment

OBJECTIVE

Categorization and risk stratification of endometrial carcinomas is inadequate; histomorphologic assessment shows considerable interobserver variability, and risk of metastases and recurrence can only be derived after surgical staging. We have developed a Proactive Molecular Risk classification tool for Endometrial cancers (ProMisE) that identifies four distinct prognostic subgroups. Our objective was to assess whether molecular classification could be performed on diagnostic endometrial specimens obtained prior to surgical staging and its concordance with molecular classification performed on the subsequent hysterectomy specimen.

METHODS

Sequencing of tumors for exonuclease domain mutations (EDMs) in POLE and immunohistochemistry for mismatch repair (MMR) proteins and p53 were applied to both pre- and post-staging archival specimens from 60 individuals to identify four molecular subgroups: MMR-D, POLE EDM, p53 wild type, p53 abn (abnormal). Three gynecologic subspecialty pathologists assigned histotype and grade to a subset of samples. Concordance of molecular and clinicopathologic subgroup assignments were determined, comparing biopsy/curetting to hysterectomy specimens.

RESULTS

Complete molecular and pathologic categorization was achieved in 57 cases. Concordance metrics for pre- vs. post-staging endometrial samples categorized by ProMisE were highly favorable; average per ProMisE class sensitivity(0.9), specificity(0.96), PPV(0.9), NPV(0.96) and kappa statistic 0.86(95%CI, 0.72-0.93), indicating excellent agreement. We observed the highest level of concordance for 'p53 abn' tumors, the group associated with the worst prognosis. In contrast, grade and histotype assignment from original pathology reports pre- vs. post-staging showed only moderate levels of agreement (kappa=0.55 and 0.44 respectively); even with subspecialty pathology review only moderate levels of agreement were observed.

CONCLUSION

Molecular classification can be achieved on diagnostic endometrial samples and accurately predicts the molecular features in the final hysterectomy specimens, demonstrating concordance superior to grade and histotype. This biologically relevant information, available at initial diagnosis, has the potential to inform management (surgery, adjuvant therapy) from the earliest time point in cancer care.

Stratification of endometrioid endometrial cancer patients into risk levels using somatic mutations

OBJECTIVE

Patients with endometrioid endometrial cancer are stratified as high risk and low risk for extrauterine disease by surgical staging. Since patients with low-grade, minimally invasive disease do not benefit from comprehensive staging, pre-surgery stratification into a risk category may prevent unnecessary surgical staging in low risk patients. Our objective was to develop a predictive model to identify risk levels using somatic mutations that could be used preoperatively.

METHODS

We classified endometrioid endometrial cancer patients in The Cancer Genome Atlas (TCGA) dataset into high risk and low risk categories: high risk patients presented with stage II, III or IV disease or stage I with high-intermediate risk features, whereas low risk patients consisted of the remaining stage I patients with either no myometrial invasion or low-intermediate risk features. Three strategies were used to build the prediction model: 1) mutational status for each gene; 2) number of somatic mutations for each gene; and 3) variant allele frequencies for each somatic mutation for each gene.

RESULTS

Each prediction strategy had a good performance, with an area under the curve (or AUC) between 61% and 80%. Analysis of variant allele frequency produced a superior prediction model for risk levels of endometrial cancer as compared to the other two strategies, with an AUC=91%. Lasso and Ridge methods identified 53 mutations that together had the highest predictability for high risk endometrioid endometrial cancer.

CONCLUSIONS

This prediction model will assist future retrospective and prospective studies to categorize endometrial cancer patients into high risk and low risk in the preoperative setting.

Improved Risk Assessment by Integrating Molecular and Clinicopathological Factors in Early-stage Endometrial Cancer-Combined Analysis of the PORTEC Cohorts

PURPOSE

Recommendations for adjuvant treatment for women with early-stage endometrial carcinoma are based on clinicopathologic features. Comprehensive genomic characterization defined four subgroups: p53-mutant, microsatellite instability (MSI), POLE-mutant, and no specific molecular profile (NSMP). We aimed to confirm the prognostic capacity of these subgroups in large randomized trial populations, investigate potential other prognostic classifiers, and integrate these into an integrated molecular risk assessment guiding adjuvant therapy.

EXPERIMENTAL DESIGN

Analysis of MSI, hotspot mutations in 14 genes including POLE, protein expression of p53, ARID1a, β-catenin, L1CAM, PTEN, ER, and PR was undertaken on 947 available early-stage endometrioid endometrial carcinomas from the PORTEC-1 and -2 trials, mostly high-intermediate risk (n = 614). Prognostic value was determined using univariable and multivariable Cox proportional hazard models. AUCs of different risk stratification models were compared.

RESULTS

Molecular analyses were feasible in >96% of the patients and confirmed the four molecular subgroups: p53-mutant (9%), MSI (26%), POLE-mutant (6%), and NSMP (59%). Integration of prognostic molecular alterations with established clinicopathologic factors resulted in a stronger model with improved risk prognostication. Approximately 15% of high-intermediate risk patients had unfavorable features (substantial lymphovascular space invasion, p53-mutant, and/or >10% L1CAM), 50% favorable features (POLE-mutant, NSMP being microsatellite stable, and CTNNB1 wild-type), and 35% intermediate features (MSI or CTNNB1-mutant).

CONCLUSIONS

Integrating clinicopathologic and molecular factors improves the risk assessment of patients with early-stage endometrial carcinoma. Assessment of this integrated risk profile is feasible in daily practice, and holds promise to reduce both overtreatment and undertreatment. Clin Cancer Res; 22(16); 4215-24. ©2016 AACR.

A clinically applicable molecular-based classification for endometrial cancers

BACKGROUND

Classification of endometrial carcinomas (ECs) by morphologic features is inconsistent, and yields limited prognostic and predictive information. A new system for classification based on the molecular categories identified in The Cancer Genome Atlas is proposed.

METHODS

Genomic data from the Cancer Genome Atlas (TCGA) support classification of endometrial carcinomas into four prognostically significant subgroups; we used the TCGA data set to develop surrogate assays that could replicate the TCGA classification, but without the need for the labor-intensive and cost-prohibitive genomic methodology. Combinations of the most relevant assays were carried forward and tested on a new independent cohort of 152 endometrial carcinoma cases, and molecular vs clinical risk group stratification was compared.

RESULTS

Replication of TCGA survival curves was achieved with statistical significance using multiple different molecular classification models (16 total tested). Internal validation supported carrying forward a classifier based on the following components: mismatch repair protein immunohistochemistry, POLE mutational analysis and p53 immunohistochemistry as a surrogate for 'copy-number' status. The proposed molecular classifier was associated with clinical outcomes, as was stage, grade, lymph-vascular space invasion, nodal involvement and adjuvant treatment. In multivariable analysis both molecular classification and clinical risk groups were associated with outcomes, but differed greatly in composition of cases within each category, with half of POLE and mismatch repair loss subgroups residing within the clinically defined 'high-risk' group. Combining the molecular classifier with clinicopathologic features or risk groups provided the highest C-index for discrimination of outcome survival curves.

CONCLUSIONS

Molecular classification of ECs can be achieved using clinically applicable methods on formalin-fixed paraffin-embedded samples, and provides independent prognostic information beyond established risk factors. This pragmatic molecular classification tool has potential to be used routinely in guiding treatment for individuals with endometrial carcinoma and in stratifying cases in future clinical trials.

Clinical significance of COX-2, GLUT-1 and VEGF expressions in endometrial cancer tissues

OBJECTIVE

To analyze the clinical significance of COX-2, GLUT-1 and VEGF expressions in endometrial cancer tissues.

METHODS

One hundred and eight tissue samples from the patients with endometrial cancer enrolled in our hospital from August 2011 to July 2014 were selected, including 60 normal tissue samples (normal group), 60 neoplastic tissue samples (neoplastic group) and 60 cancer tissue samples (cancer group). All the samples were subjected to immunohistochemical assay to detect the expressions of COX-2, GLUT-1 and VEGF. The clinical data were also investigated for correlation analysis.

RESULTS

The positive rates of COX-2 in normal group, neoplastic group and cancer groups were 3.3%, 21.7% and 55.0% respectively. The positive rates of GLUT-1 in normal group, neoplastic group and cancer groups were 3.3%, 25.0% and 70.0% respectively. The positive rates of VEGF in normal group, neoplastic group and cancer groups were 1.7%, 23.3% and 63.3% respectively. With increasing stage of such cancer, decreasing degree of differentiation and lymphatic metastasis, the positive expression rates of COX-2, GLUT-1 and VEGF proteins were raised significantly (P<0.05). Spearman's correlation analysis showed that the expressions of COX-2 and GLUT-1 (r=0.207, P<0.05), COX-2 and VEGF (r=0.243, P<0.05), as well as GLUT-1 and VEGF (r=0.758, P<0.05) were positively correlated.

CONCLUSION

COX-2, GLUT-1 and VEGF were highly prominent in endometrial cancer, especially in the patients with low degree of differentiation, late stage and metastasis. They functioned synergistically in the onset and progression of this cancer.

Refining prognosis and identifying targetable pathways for high-risk endometrial cancer; a TransPORTEC initiative

This study aimed to investigate whether molecular analysis can be used to refine risk assessment, direct adjuvant therapy, and identify actionable alterations in high-risk endometrial cancer. TransPORTEC, an international consortium related to the PORTEC3 trial, was established for translational research in high-risk endometrial cancer. In this explorative study, routine molecular analyses were used to detect prognostic subgroups: p53 immunohistochemistry, microsatellite instability and POLE proofreading mutation. Furthermore, DNA was analyzed for hotspot mutations in 13 additional genes (BRAF, CDKNA2, CTNNB1, FBXW7, FGFR2, FGFR3, FOXL2, HRAS, KRAS, NRAS, PIK3CA, PPP2R1A, and PTEN) and protein expression of ER, PR, PTEN, and ARID1a was analyzed. Rates of distant metastasis, recurrence-free, and overall survival were calculated using the Kaplan-Meier method and log-rank test. In total, samples of 116 high-risk endometrial cancer patients were included: 86 endometrioid; 12 serous; and 18 clear cell. For endometrioid, serous, and clear cell cancers, 5-year recurrence-free survival rates were 68%, 27%, and 50% (P=0.014) and distant metastasis rates 23%, 64%, and 50% (P=0.001), respectively. Four prognostic subgroups were identified: (1) a group of p53-mutant tumors; (2) microsatellite instable tumors; (3) POLE proofreading-mutant tumors; and (4) a group with no specific molecular profile (NSMP). In group 3 (POLE-mutant; n=14) and group 2 (microsatellite instable; n=19) patients, no distant metastasis occurred, compared with 50% distant metastasis rate in group 1 (p53-mutant; n=36) and 39% in group 4 (NSMP; P<0.001). Five-year recurrence-free survival was 93% and 95% for group 3 (POLE-mutant) and group 2 (microsatellite instable) vs 42% (group 1, p53-mutant) and 52% (group 4, NSMP; P<0.001). Targetable FBXW7 and FGFR2 mutations (6%), alterations in the PI3K-AKT pathway (60%) and hormone receptor positivity (45%) were frequently found. In conclusion, molecular analysis of high-risk endometrial cancer identifies four distinct prognostic subgroups, with potential therapeutic implications. High frequencies of targetable alterations were identified and may serve as targets for individualized treatment.