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ObjectiveManagement of endometrial cancer is advancing, with accurate staging crucial for guiding treatment decisions. Understanding sentinel lymph node (SLN) involvement rates across molecular subgroups is essential. To evaluate SLN involvement in early-stage (International Federation of Gynecology and Obstetrics 2009 I–II) endometrial cancer, considering molecular subtypes and new European Society of Gynaecological Oncology (ESGO) risk classification.MethodsThe SENECA study retrospectively reviewed data from 2139 women with stage I–II endometrial cancer across 66 centers in 16 countries. Patients underwent surgery with SLN assessment following ESGO guidelines between January 2021 and December 2022. Molecular analysis was performed on pre-operative biopsies or hysterectomy specimens.ResultsAmong the 2139 patients, the molecular subgroups were as follows: 272 (12.7%) p53 abnormal (p53abn, 1191 (55.7%) non-specific molecular profile (NSMP), 581 (27.2%) mismatch repair deficient (MMRd), 95 (4.4%) POLE mutated (POLE-mut). Tracer diffusion was detected in, at least one side, in 97.2% of the cases; with a bilateral diffusion observed in 82.7% of the cases. By ultrastaging (90.7% of the cases) or one-step nucleic acid amplification (198 (9.3%) of the cases), 205 patients were identified with affected sentinel lymph nodes, representing 9.6% of the sample. Of these, 139 (67.8%) had low-volume metastases (including micrometastases, 42.9%; and isolated tumor cells, 24.9%) while 66 (32.2%) had macrometastases. Significant differences in SLN involvement were observed between molecular subtypes, with p53abn and MMRd groups having the highest rates (12.50% and 12.40%, respectively) compared with NSMP (7.80%) and POLE-mut (6.30%), (p=0.004); (p53abn, OR=1.69 (95% CI 1.11 to 2.56), p=0.014; MMRd, OR=1.67 (95% CI 1.21 to 2.31), p=0.002). Differences were also noted among ESGO risk groups (2.84% for low-risk patients, 6.62% for intermediate-risk patients, 21.63% for high–intermediate risk patients, and 22.51% for high-risk patients; p<0.001).ConclusionsOur study reveals significant differences in SLN involvement among patients with early-stage endometrial cancer based on molecular subtypes. This underscores the importance of considering molecular characteristics for accurate staging and optimal management decisions.

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.

Endometrial cancer is the most common gynaecological malignancy in Europe and North America. Traditional classification of endometrial carcinoma is based either on clinical and endocrine features (eg, types I and II) or on histopathological characteristics (eg, endometrioid, serous, or clear-cell adenocarcinoma). Subtypes defined by the different classification systems correlate to some extent, but there is substantial heterogeneity in biological, pathological, and molecular features within tumour types from both classification systems. In this Review we provide an overview of traditional and newer genomic classifications of endometrial cancer. We discuss how a classification system that incorporates genomic and histopathological features to define biologically and clinically relevant subsets of the disease would be useful. Such integrated classification might facilitate development of treatments tailored to specific disease subgroups and could potentially enable delivery of precision medicine to patients with endometrial cancer.

Endometrial cancer is primarily treated with surgery. Adjuvant treatment strategies for endometrial cancer, such as external beam pelvic radiotherapy, vaginal brachytherapy, chemotherapy, and combined chemotherapy and radiotherapy, have been studied in several randomized trials. Adjuvant treatment is currently based on the presence of clinico-pathological risk factors. Low-risk disease is adequately managed with surgery alone. In high-intermediate risk endometrial cancer, adjuvant vaginal brachytherapy is recommended to maximize local control, with only mild side effects and without impact on quality of life. For high-risk endometrial cancer, recent large randomized trials support the use of pelvic radiotherapy, especially in stage I–II endometrial cancer with risk factors. For women with serous cancers and those with stage III disease, chemoradiation increased both recurrence-free and overall survival, while GOG-258 showed similar recurrence-free survival compared with six cycles of chemotherapy alone, but with better pelvic and para-aortic nodal control with combined chemotherapy and radiotherapy. Recent molecular studies, most notably the work from The Cancer Genome Atlas (TCGA) project, have shown that four endometrial cancer molecular classes can be distinguished; POLE ultra-mutated, microsatellite instable hypermutated, copy-number-low, and copy-number-high. Subsequent studies, using surrogate markers to identify groups analogous to TCGA sub-classes, showed that all four endometrial cancer sub-types are found across all stages, histological types, and grades. Moreover, the molecular sub-groups have proved to have a stronger prognostic impact than histo-pathological tumor characteristics. This introduces an new era of molecular classification based diagnostics and treatment approaches. Integration of the molecular factors and new therapeutic targets will lead to molecular-integrated adjuvant treatment including targeted treatments, which are the rationale of new and ongoing trials. This review presents an overview of current adjuvant treatment strategies in endometrial cancer, highlights the development and evaluation of a molecular-integrated risk profile, and briefly discusses ongoing developments in targeted treatment.

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.

We performed an integrated genomic, transcriptomic and proteomic characterization of 373 endometrial carcinomas using array- and sequencing-based technologies. Uterine serous tumours and ∼25% of high-grade endometrioid tumours had extensive copy number alterations, few DNA methylation changes, low oestrogen receptor/progesterone receptor levels, and frequent TP53 mutations. Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN , CTNNB1 , PIK3CA , ARID1A and KRAS and novel mutations in the SWI/SNF chromatin remodelling complex gene ARID5B . A subset of endometrioid tumours that we identified had a markedly increased transversion mutation frequency and newly identified hotspot mutations in POLE . Our results classified endometrial cancers into four categories: POLE ultramutated, microsatellite instability hypermutated, copy-number low, and copy-number high. Uterine serous carcinomas share genomic features with ovarian serous and basal-like breast carcinomas. We demonstrated that the genomic features of endometrial carcinomas permit a reclassification that may affect post-surgical adjuvant treatment for women with aggressive tumours. An integrative genomic analysis of several hundred endometrial carcinomas shows that a minority of tumour samples carry copy number alterations or TP53 mutations and many contain key cancer-related gene mutations, such as those involved in canonical pathways and chromatin remodelling; a reclassification of endometrial tumours into four distinct types is proposed, which may have an effect on patient treatment regimes. Reclassification of uterine carcinomas This paper from The Cancer Genome Atlas Research Network presents an in-depth genome-wide analysis of endometrial (uterine) carcinomas from more than 350 patients. Based on a series of genomic features including newly identified hotspot mutations in the DNA polymerase gene POLE , and novel mutations in the ARID5B DNA-binding protein, the authors propose a reclassification of endometrial tumours into four distinct types. This might have clinical relevance for post-surgical adjuvant treatment of women with aggressive tumours.

Although many recent advancements have been made in women’s health, perhaps one of the most neglected areas of research is the diagnosis and treatment of high-grade endometrial cancer (EnCa). The molecular classification of EnCa in concert with histology was a major step forward. The integration of profiling for mismatch repair deficiency and Human Epidermal Growth Factor 2 (HER2) overexpression, can further inform treatment options, especially for drug resistant recurrent disease. Recent early phase trials suggest that regardless of subtype, combination therapy with agents that have distinct mechanisms of action is a fruitful approach to the treatment of high-grade EnCa. Unfortunately, although the importance of diagnosis and treatment of high-grade EnCa is well recognized, it is understudied compared to other gynecologic and breast cancers. There remains a tremendous need to couple molecular profiling and biomarker development with promising treatment options to inform new treatment strategies with higher efficacy and safety for all who suffer from high-grade recurrent EnCa.

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. Trans PORTEC, 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.

BackgroundThe newly developed Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE) has consistently been shown to be prognostically significant in endometrial carcinomas (EC). Recently, we and others have demonstrated L1 cell-adhesion molecule (L1CAM) to be a significant indicator of high-risk disease in EC. In the current study, it was our aim to determine the prognostic significance of aberrant L1CAM expression in ProMisE subgroups in a large, single centre, population-based EC cohort.MethodsProMisE (POLE; MMR-D; p53 wt/NSMP; p53 abn) classification results from a cohort of 452 EC were available for analysis. L1CAM expression was studied by immunohistochemistry on whole slides. Correlations between clinicopathological data and survival were calculated.ResultsExpression of L1CAM was most frequent in p53 abnormal tumours (80%). L1CAM status was predictive of worse outcome among tumours with no specific molecular profile (p53 wt/NSMP) (p < 0.0001). Among p53 wt/NSMP EC, L1CAM remained a significant prognosticator for disease-specific survival after multivariate analysis (p = 0.035).ConclusionL1CAM status was able to significantly stratify risk among tumours of the large p53 wt/NSMP ProMisE subgroup of EC. Furthermore, our study confirms a highly significant correlation between mutation-type p53 immunostaining and abnormal L1CAM expression in EC.

Endometrial cancer (EC) is the most common gynecological malignancy, yet reliable screening and diagnostic approaches remain limited. We developed a weakly supervised deep multi-instance learning model (DSMIL) to classify hematoxylin and eosin-stained whole-slide images (WSIs) of endometrial tissue. A total of 885 WSIs from 442 patients, including EC, atypical endometrial hyperplasia (AEH), endometrial hyperplasia without atypia (EH), and normal endometrium (NE), were analyzed. DSMIL achieved an average AUROC of 0.9776 for four-class classification, with inter-class AUROCs of 0.9876 for EC, 0.9600 for AEH, 0.9771 for EH, and 0.9855 for NE, and outperformed other algorithms such as TransMSL, CLAM, and ABMIL (average accuracy = 0.8914). Attention heatmaps highlighted regions associated with pathological features, while nnU-Net v2 combined with HoverNet enabled identification of atypical glandular epithelial cells, which showed increased density, size, and perimeter but reduced axis ratios compared with normal cells. These results suggest that DSMIL provides a reliable computational pathology approach for the classification of endometrial lesions and the characterization of atypical cells.