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Uterine carcinosarcoma (UCS) is a highly aggressive gynecologic malignancy. Recurrent or persistent/progressive disease is usually fatal. We aimed to investigate the management and prognosis of these patients. Clinical records of UCS patients from June 1987 to April 2020 were retrospectively reviewed. The stage was re-assigned with the FIGO 2009 staging system. Univariate and multivariate analyses were used to identify the independent predictors of survival after recurrence (SAR) and cancer-specific survival (CSS). Of the 168 patients, 98 experienced treatment failure. The median time to treatment failure (TTF) was 8.1 months (range: 0.0–89.1). The median follow-up time of censored patients was 32.0 months (range: 16.8–170.7). The 5-year SAR rates of those with recurrent or persistent/progressive disease were 7.6%. On multivariate analysis, salvage therapy mainly using radiotherapy (HR 0.27, 95% CI: 0.10–0.71) or chemotherapy (HR 0.41, 95% CI: 0.24–0.72) or chemoradiotherapy (CRT) (HR 0.33, 95% CI: 0.15–0.75) were associated with improved SAR, whereas disseminated recurrence was associated with significantly worse SAR (HR 3.94, 95% CI: 1.67–9.31, p = 0.002). Salvage therapy using radiotherapy or chemotherapy or CRT significantly improved SAR. Surgery significantly improved CSS but not SAR, adjusting for confounding factors.

Objective: Lynch syndrome (LS) is a hereditary cancer predisposition syndrome with a significantly increased risk of colorectal and endometrial cancers. Current standard practice involves universal screening for LS in patients with newly diagnosed colorectal or endometrial cancer using a multi-step screening protocol (MSP). However, MSP may not always accurately identify LS cases. To address this limitation, we compared the diagnostic performance of immediate germline sequencing (IGS) with MSP in a high-risk group. Methods: A total of 31 Taiwanese women with synchronous or metachronous endometrial and colorectal malignancies underwent MSP which included immunohistochemical staining of DNA mismatch repair (MMR) proteins, MLH1 promoter hypermethylation analysis, and germline sequencing to identify pathogenic variants. All patients who were excluded during MSP received germline sequencing for MMR genes to simulate IGS for the detection of LS. Results: Our findings indicate that IGS surpassed MSP in terms of diagnostic yield (29.0% vs. 19.4%, respectively) and sensitivity (90% vs. 60%, respectively). Specifically, IGS successfully identified nine LS cases, which is 50% more than the number detected through MSP. Additionally, germline methylation analysis revealed one more LS case with constitutional MLH1 promoter hypermethylation, bringing the total LS cases to ten (32.3%). Intriguingly, we observed no significant differences in clinical characteristics or overall survival between patients with and without LS in our cohort. Conclusion: Our study suggests that IGS may potentially offer a more effective approach compared to MSP in identifying LS among high-risk patients. This advantage is evident when patients have been pre-selected utilizing specific clinical criteria. [ABSTRACT FROM AUTHOR]

The histological criteria for classifying endometrial hyperplasia (EH) are based on architectural crowding and nuclear atypia; however, diagnostic agreement among pathologists is poor. We investigated molecular biomarkers of endometrial cancer (EC) risk in women with simple hyperplasia or complex hyperplasia without atypia (SH/CH-nonA). Forty-nine patients with EC preceded by SH/CH-nonA were identified, of which 23 were excluded (15 with complex atypical hyperplasia (CAH), six not consenting, one with a diagnosis p < 0.05, fold change >4) between the control (n = 12) and case (n = 6) patients. Multiplex RT-qPCR for the 20 miRNAs in the expanded cohort (94 control and 25 case patients) led to the validation of miR-30a-3p (p = 0.0009), miR-141 (p < 0.0001), miR-200a (p < 0.0001), and miR-200b (p < 0.0001) as relevant biomarkers, among which miR-141, miR-200a, and miR-200b regulate the expression of phosphatase and tensin homolog (PTEN). For the prediction of EC, the area under the curve for miR-30a-3p, miR-141, miR-200a, and miR-200b was 0.623, 0.754, 0.783, and 0.704, respectively. The percentage of complete PTEN loss was significantly higher in the case group than in the control group (24% vs. 0%, p < 0.001, Fisher’s exact test). A combination of complete PTEN loss and miR-200a provided optimal prediction performance (sensitivity = 0.760; specificity = 1.000; positive predictive value = 1.000; negative predictive value = 0.937; accuracy = 0.947). MiR-30a-3p, miR-141, miR-200a, miR-200b, and complete PTEN loss may be useful tissue biomarkers for predicting EC risk among patients with SH/CH-nonA.

Precise risk stratification in lymphadenectomy is important for patients with endometrial cancer (EC), to balance the therapeutic benefit against the operation-related morbidity and mortality. We aimed to investigate added values of computer-aided segmentation and machine learning based on clinical parameters and diffusion-weighted imaging radiomics for predicting lymph node (LN) metastasis in EC. This prospective observational study included 236 women with EC (mean age ± standard deviation, 51.2 ± 11.6 years) who underwent magnetic resonance (MR) imaging before surgery during July 2010–July 2018, randomly split into training (n = 165) and test sets (n = 71). A decision-tree model was constructed based on mean apparent diffusion coefficient (ADC) value of the tumor (cutoff, 1.1 × 10−3 mm2/s), skewness of the relative ADC value (cutoff, 1.2), short-axis diameter of LN (cutoff, 1.7 mm) and skewness ADC value of the LN (cutoff, 7.2 × 10−2), as well as tumor grade (1 vs. 2 and 3), and clinical tumor size (cutoff, 20 mm). The sensitivity and specificity of the model were 94% and 80% for the training set and 86%, 78% for the independent testing set, respectively. The areas under the receiver operating characteristics curve (AUCs) of the decision-tree was 0.85—significantly higher than the mean ADC model (AUC = 0.54) and LN short-axis diameter criteria (AUC = 0.62) (both p < 0.0001). We concluded that a combination of clinical and MR radiomics generates a prediction model for LN metastasis in EC, with diagnostic performance surpassing the conventional ADC and size criteria.

Uterine carcinosarcoma (UCS) is a highly aggressive gynecologic malignancy. Recurrent or persistent/progressive disease is usually fatal. We aimed to investigate the management and prognosis of these patients. Clinical records of UCS patients from June 1987 to April 2020 were retrospectively reviewed. The stage was re-assigned with the FIGO 2009 staging system. Univariate and multivariate analyses were used to identify the independent predictors of survival after recurrence (SAR) and cancer-specific survival (CSS). Of the 168 patients, 98 experienced treatment failure. The median time to treatment failure (TTF) was 8.1 months (range: 0.0–89.1). The median follow-up time of censored patients was 32.0 months (range: 16.8–170.7). The 5-year SAR rates of those with recurrent or persistent/progressive disease were 7.6%. On multivariate analysis, salvage therapy mainly using radiotherapy (HR 0.27, 95% CI: 0.10–0.71) or chemotherapy (HR 0.41, 95% CI: 0.24–0.72) or chemoradiotherapy (CRT) (HR 0.33, 95% CI: 0.15–0.75) were associated with improved SAR, whereas disseminated recurrence was associated with significantly worse SAR (HR 3.94, 95% CI: 1.67–9.31, p = 0.002). Salvage therapy using radiotherapy or chemotherapy or CRT significantly improved SAR. Surgery significantly improved CSS but not SAR, adjusting for confounding factors. [ABSTRACT FROM AUTHOR]

Synchronous endometrial and ovarian carcinomas (SEOCs) that share the same endometrioid histology are generally considered as the result of metastatic spread from one organ to another. However, SEOCs with different histologies are regarded as distinct primary lesions that arise independently from each other. This study was undertaken to compare the mutational landscape of SEOCs with different histologies to confirm or refute the hypothesis of an independent origin. Four patients with synchronous uterine endometrioid carcinoma (UEMC) and ovarian clear cell carcinoma (OCCC) were examined. UEMCs were accompanied by endometrial hyperplasia/endometrioid intraepithelial neoplasia, whereas endometriosis was evident in two cases. Paired UEMC and OCCC specimens were subjected to mutation analysis with massively parallel sequencing. Surprisingly, we found that 50% (2/4) of paired SEOCs with different histologies shared the same somatic mutations, some of which localized in cancer driver genes. Clonality analyses indicated that these tumors were clonally related to each other. Notably, 75% (3/4) of the study patients had Lynch syndrome. The cancer-specific survival figures of patients with synchronous UEMCs and OCCCs were more favorable than those observed in a historical cohort of patients with isolated stage 2/3 OCCCs. Taken together, we set forth a potential explanation that considers clonally related SEOCs as a result of "precursor escape" — whereby precursor cells of endometrial cancer spread beyond the uterus to reach the pelvis and eventually evolve into an OCCC under an increasing mutational burden. Key messages: • SEOCs characterized by different histologies are rare. • All cases of SEOCs were accompanied by endometrial hyperplasia. • Fifty percent of SEOCs were clonally related to each other. • Shared mutations in cancer driver genes were evident among SEOCs. • Clonally related SEOCs may be a result of "precursor escape." • Lynch syndrome is highly prevalent in patients with UEMC and synchronous OCCC. • The prognosis of synchronous UEMC and OCCC was favorable. [ABSTRACT FROM AUTHOR]

The histological criteria for classifying endometrial hyperplasia (EH) are based on architectural crowding and nuclear atypia; however, diagnostic agreement among pathologists is poor. We investigated molecular biomarkers of endometrial cancer (EC) risk in women with simple hyperplasia or complex hyperplasia without atypia (SH/CH-nonA). Forty-nine patients with EC preceded by SH/CH-nonA were identified, of which 23 were excluded (15 with complex atypical hyperplasia (CAH), six not consenting, one with a diagnosis < 6 months prior, and one lost to follow-up). The EH tissues of these patients were compared with those of patients with SH/CH-nonA that did not progress to EC (control) through microRNA (miRNA) array analysis, and the results were verified in an expanded cohort through reverse transcription-quantitative polymerase chain reaction (RT-qPCR). MiRNA arrays analyses revealed 20 miRNAs that differed significantly (p < 0.05, fold change > 4) between the control (n = 12) and case (n = 6) patients. Multiplex RT-qPCR for the 20 miRNAs in the expanded cohort (94 control and 25 case patients) led to the validation of miR-30a-3p (p = 0.0009), miR-141 (p < 0.0001), miR-200a (p < 0.0001), and miR-200b (p < 0.0001) as relevant biomarkers, among which miR-141, miR-200a, and miR-200b regulate the expression of phosphatase and tensin homolog (PTEN). For the prediction of EC, the area under the curve for miR-30a-3p, miR-141, miR-200a, and miR-200b was 0.623, 0.754, 0.783, and 0.704, respectively. The percentage of complete PTEN loss was significantly higher in the case group than in the control group (24% vs. 0%, p < 0.001, Fisher's exact test). A combination of complete PTEN loss and miR-200a provided optimal prediction performance (sensitivity = 0.760; specificity = 1.000; positive predictive value = 1.000; negative predictive value = 0.937; accuracy = 0.947). MiR-30a-3p, miR-141, miR-200a, miR-200b, and complete PTEN loss may be useful tissue biomarkers for predicting EC risk among patients with SH/CH-nonA. [ABSTRACT FROM AUTHOR]

Our aim was to investigate the outcomes and prognostic factors after treatment failure of endometrial cancer.A total of 923 endometrial cancer patients were treated between 2000 and 2010, of which 109 experienced treatment failure. Treatment failure was defined as relapse after complete removal of all cancerous lesions or persistent/progressive disease despite treatment. Variables including clinicopathological features at initial treatment, type of primary treatment, failure pattern, salvage treatment, and outcomes were analyzed. Kaplan-Meier survival curves were compared with log-rank test. Cox proportional hazards regression model was used to identify significant prognostic factors.Eighteen cases with persistent/progressive disease died shortly from primary diagnosis (1-23 months). The remaining 91 patients had recurrences in vagina only (8.8%), pelvis (3.3%), distant (63.7%), and combined pelvic-distant sites (24.2%). Median time to recurrence was 13.3 months (3.2-97.2 months). The median follow-up after recurrence of survivors was 60.5 months (10.6-121.7 months). The median survival after recurrence (SAR) was 20.3 months (1.9-121.7 months) with 5-year SAR rate of 32.4%. By multivariate analysis, initial stage II to IV (hazards ratio [HR], 3.41; 1.53-7.60; P = 0.003), type II histology (HR, 2.50; 1.28-4.90; P = 0.008), positive peritoneal cytology (HR, 2.23; 1.07-4.68; P = 0.033), and recurrence at multiple sites (HR, 2.51; 1.30-4.84; P = 0.006) were significantly associated with poor SAR. The 5-year SAR rates in patients with solitary vaginal, nodal/liver, or pulmonary/bony recurrence were 83.3%, 50.5%, and 24.2%, respectively. Ten cases with resectable or irradiatable recurrence at multiple sites or multiple relapses attained SAR greater than 5 years after multimodality salvage therapy.Initial stage II to IV, type 2 histology, positive cytology, and recurrence at multiple sites were significant poor prognostic factors. Curative intent salvage therapy remains a viable option for cases with resectable or irradiatable multiple recurrences and solitary distant metastasis. [ABSTRACT FROM AUTHOR]

Simple Summary: Computer-aided segmentation and machine learning added values of clinical parameters and diffusion-weighted imaging radiomics for predicting nodal metastasis in endometrial cancer, with a diagnostic performance superior to criteria based on lymph node size or apparent diffusion coefficient. Precise risk stratification in lymphadenectomy is important for patients with endometrial cancer (EC), to balance the therapeutic benefit against the operation-related morbidity and mortality. We aimed to investigate added values of computer-aided segmentation and machine learning based on clinical parameters and diffusion-weighted imaging radiomics for predicting lymph node (LN) metastasis in EC. This prospective observational study included 236 women with EC (mean age ± standard deviation, 51.2 ± 11.6 years) who underwent magnetic resonance (MR) imaging before surgery during July 2010–July 2018, randomly split into training (n = 165) and test sets (n = 71). A decision-tree model was constructed based on mean apparent diffusion coefficient (ADC) value of the tumor (cutoff, 1.1 × 10−3 mm2/s), skewness of the relative ADC value (cutoff, 1.2), short-axis diameter of LN (cutoff, 1.7 mm) and skewness ADC value of the LN (cutoff, 7.2 × 10−2), as well as tumor grade (1 vs. 2 and 3), and clinical tumor size (cutoff, 20 mm). The sensitivity and specificity of the model were 94% and 80% for the training set and 86%, 78% for the independent testing set, respectively. The areas under the receiver operating characteristics curve (AUCs) of the decision-tree was 0.85—significantly higher than the mean ADC model (AUC = 0.54) and LN short-axis diameter criteria (AUC = 0.62) (both p < 0.0001). We concluded that a combination of clinical and MR radiomics generates a prediction model for LN metastasis in EC, with diagnostic performance surpassing the conventional ADC and size criteria. [ABSTRACT FROM AUTHOR]