Endometrial cancer (EC) is the most common gynaecologic malignancy in developed countries. The main challenge in EC management is to correctly estimate the risk of metastases at diagnosis and the risk to develop recurrences in the future. Risk stratification determines the need for surgical staging and adjuvant treatment. Detection of occult, microscopic metastases upstages patients, provides important prognostic information and guides adjuvant treatment. The molecular classification subdivides EC into four prognostic subgroups: POLE ultramutated; mismatch repair deficient (MMRd); nonspecific molecular profile (NSMP); and TP53 mutated (p53abn). How surgical staging should be adjusted based on preoperative molecular profiling is currently unknown. Moreover, little is known whether and how other known prognostic biomarkers affect prognosis prediction independent of or in addition to these molecular subgroups. This review summarizes the factors incorporated in surgical staging (i.e., peritoneal washing, lymph node dissection, omentectomy and peritoneal biopsies), and its impact on prognosis and adjuvant treatment decisions in an era of molecular classification of EC. Moreover, the relation between FIGO stage and molecular classification is evaluated including the current gaps in knowledge and future perspectives.

Endometrial cancer incidence is rising and current diagnostics often require invasive biopsy procedures. DNA methylation marker analysis of minimally‐ and non‐invasive sample types could provide an easy‐to‐apply and patient‐friendly alternative to determine cancer risk. Here, we compared the performance of DNA methylation markers to detect endometrial cancer in urine, cervicovaginal self‐samples and clinician‐taken cervical scrapes. Paired samples were collected from 103 patients diagnosed with stage I to IV endometrial cancer. Urine and self‐samples were collected at home. All samples were tested for nine DNA methylation markers using quantitative methylation‐specific PCR. Methylation levels measured in endometrial cancer patients were compared to unpaired samples of 317 healthy controls. Diagnostic performances were evaluated by univariable and multivariable logistic regression analysis, followed by leave‐one‐out cross‐validation. Each methylation marker showed significantly higher methylation levels in all sample types of endometrial cancer patients compared to healthy controls (P < .01). Optimal three‐marker combinations demonstrated excellent diagnostic performances with area under the receiver operating curve values of 0.95 (95% CI: 0.92‐0.98), 0.94 (0.90‐0.97) and 0.97 (0.96‐0.99), for endometrial cancer detection in urine, self‐samples and scrapes, respectively. Sensitivities ranged from 89% to 93% at specificities of 90% to 92%. Virtually equal performances were obtained after cross‐validation and excellent diagnostic performances were maintained for stage I endometrial cancer detection. Our study shows the value of methylation analysis in patient‐friendly sample types for endometrial cancer detection of all stages. This approach has great potential to screen patient populations at risk for endometrial cancer.

The aim was to investigate the incidence of sentinel lymph node (SLN) metastases and the contribution of SLN mapping in presumed low- and intermediate-risk endometrial cancer (EC). A multicenter, prospective cohort study in presumed low- and intermediate-risk EC patients was performed. Patients underwent SLN mapping using cervical injections of indocyanine green and a minimally invasive hysterectomy with bilateral salpingo-oophorectomy. The primary outcome was the incidence of SLN metastases, leading to adjusted adjuvant treatment. Secondary outcomes were the SLN detection rate and the occurrence of complications. Descriptive statistics and univariate general linear model analyses were used. A total of 152 patients were enrolled, with overall and bilateral SLN detection rates of 91% and 61%, respectively. At final histology, 78.9% of patients (n = 120) had truly low- and intermediate-risk EC. Macro- and micro-metastases were present in 11.2% (n = 17/152), and three patients had isolated tumor cells (2.0%). Nine patients (5.9%) had addition of adjuvant radiotherapy based on SLN metastases only. In 2.0% of patients with high-risk disease, adjuvant therapy was more limited due to negative SLNs. This study emphasizes the importance of SLN mapping in presumed early-stage, grade 1 and 2 EC, leading to individualized adjuvant management, resulting in less undertreatment and overtreatment.

Molecular classification has reshaped risk stratification in endometrial cancer (EC), yet the relevance of tumor spread within molecular subgroups has not been reported so far. This multicenter retrospective study included 2056 EC patients treated between 1994 and 2018 across 11 European centers. All histopathological subtypes and FIGO stages were included. Tumors were classified into four molecular subgroups: POLE-mutated (POLEmut), mismatch repair deficient (MMRd), no specific molecular profile (NSMP), and TP53/p53 abnormal (p53abn). Clinical and pathological data were extracted from existing cohort databases. Patients were diagnosed with FIGO stage I (69 %), II (9 %), III (16 %), and IV (6 %), and classified into: POLEmut (8 %), MMRd (28 %), NSMP (44 %), and p53abn (21 %). The overall 5-year cancer-specific death (CSD) and recurrence rates were 16.5 % (95 % CI, 14.9 %-18.2 %) and 23.8 % (95 % CI, 22.0 %-25.7 %), respectively. In multivariable analysis cancer-specific survival (CSS) was independently associated with molecular subtype, FIGO stage, age, histopathological type, grade, lymphovascular space invasion, adjuvant therapy, residual tumor, and lymphadenectomy. FIGO stage was significantly associated with CSD also in within each molecular subgroup (p < 0.001). Patients with tumors confined to the uterus had the most favourable prognosis. Lymph node metastases significantly decreased CSS in POLEmut, MMRd, and p53abn groups. Within FIGO stage IV, molecular subtype was not significantly related to outcome. Surgical stage remains a strong prognostic factor across molecular subtypes and should be considered alongside molecular classification when tailoring adjuvant treatment in EC.

DNA methylation analysis of self‐collected samples has shown potential for primary endometrial cancer detection. Here, we aimed to explore DNA methylation testing as a non‐invasive alternative for post‐treatment surveillance. Endometrial cancer patients ( n = 43) without recurrence collected pre‐ and post‐treatment cervicovaginal self‐samples and urine at home. Additionally, 17 patients with recurrence provided these samples at the time of recurrence. Healthy controls were used as reference. In total, 207 cervicovaginal self‐samples and 203 urine samples were tested for nine markers ( ADCYAP1 , BHLHE22 , CDH13 , CDO1 , GALR1 , GHSR , HAND2 , SST and ZIC1 ) using quantitative methylation‐specific PCR. Diagnostic performance was assessed using previously established logistic regression models. In patients without recurrence, most marker levels decreased post‐treatment compared to pre‐treatment, in both sample types. DNA methylation positivity in cervicovaginal self‐samples reduced from 90.7% pre‐treatment to 19.5% post‐treatment ( p < .0001). In urine, a decrease from 80.5% to 20.9% was observed ( p < .0001). In patients with recurrence, DNA methylation levels of CDH13 , CDO1 , GALR1 , GHSR and HAND2 in cervicovaginal self‐samples, and CDO1 , GHSR and HAND2 in urine, were higher than in patients without recurrence. DNA methylation positivity was 62.5% in cervicovaginal self‐samples and 58.8% in urine among patients with any recurrence, and 100% in cervicovaginal self‐samples and 90.0% in urine of patients with a local recurrence specifically. These findings support methylation‐based testing as a promising post‐treatment surveillance method for endometrial cancer patients. This non‐invasive approach could reduce the follow‐up burden on patients and healthcare, alleviating challenges related to resource constraints while improving patient comfort.