Incidence, risk factors, and a prognostic nomogram for distant metastasis in endometrial cancer: A SEER-based study.

OBJECTIVE: To evaluate the metastatic pattern, identify the risk factors, and establish a nomogram for predicting prognosis of endometrial cancer (EC) with distant metastasis. METHODS: A retrospective cohort study of women diagnosed with EC was conducted according to the Surveillance, Epidemiology, and End Results (SEER) database during 2010-2017. Multivariate logistic analysis and Cox analysis were performed to identify the risk factors in promoting distant metastasis and predictors associated with overall survival (OS) in this particular subpopulation. A nomogram was then constructed and validated by the concordance index (C-index), the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis. RESULTS: A total of 2799 cases of distant metastasis in EC patients were identified, with an overall incidence rate of 3.74% from 2010 to 2017. Black race, unmarried status, non-endometrioid histologic types, and grade IV were significant risk factors for distant metastasis in EC patients. Meanwhile, race, histology, grade, metastasis status, surgery, lymphadenectomy, and chemotherapy were identified as independent prognostic factors for OS. A nomogram to predict 1-, 3-, and 5-year OS was established, and presented favorable accuracy and clinical applicability. Patients were further divided into high- and low-risk groups according to the model. CONCLUSION: The nomogram was developed as a highly accurate, individualized tool to better predict the prognosis of EC patients with distant metastasis, which would help clinicians to identify high-risk patients, and adjust and tailor their treatment strategies.

YAP1 affects the prognosis through the regulation of stemness in endometrial cancer.

Background: Endometrial cancer stem-like cells (ECSCs) have been proven to be responsible for recurrence, metastasis, and drug-resistance in patients with endometrial cancer. The HIPPO pathway has been shown to play an important role in the development and maintenance of stemness in a variety of tumors. While there was less research about its function in ECSCs. The aim of this study was to explore the role of YAP1, a core molecular of HIPPO pathway, in the stemness of endometrial cancer and to reveal its influence on prognosis. Methods: We collected specimens and clinical data from 774 patients with endometrial cancer to analyze the correlation between YAP1 expression and prognosis. We then examined the expression of YAP1 in ECSCs and EC cell lines (Ishikawa; HEC1-A) in vitro experiments. Changes in the stemness of cell lines were detected after YAP1 silencing by siRNA. Finally, high-throughput sequencing was used to predict the potential molecular interactions and mechanisms of YAP1's effect on stemness. Result: Down-regulation of YAP1 significantly suppresses the stemness of EC cell lines. High expression of YAP1 leads to poor prognosis in EC by regulation of stemness. Conclusion: YAP1 plays an important role in the prognosis of patients with EC by regulation of stemness.

Predicting the Recurrence of Operable Cervical Cancer Patients Based on Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) Score and Classical Clinicopathological Parameters.

Objective: The purpose of this study was to evaluate the prognostic value of hemoglobin, albumin, lymphocyte, and platelet (HALP) score in patients with operable cervical cancer, and on this basis, combined with classical clinicopathological parameters to predict the recurrence of patients. Methods: A total of 1580 patients with stage IA-IIA cervical cancer were randomly divided into training cohort (n=1054) and validation cohort (n=526) according to the predefined ratio of 2:1. In the training cohort, the receiver operating characteristic (ROC) curve and Youden index were used to determine the optimal threshold of HALP score for predicting cervical cancer recurrence. On this basis, the independent related factors with cervical cancer recurrence were screened through univariate and multivariate Cox regression analysis, and then a nomogram model was further established. The internal and external validation of the model was carried out in the training cohort and the validation cohort respectively through the consistency index (C-index) and calibration curve. Results: ROC curve and Youden index showed that the optimal threshold of HALP score for predicting cervical cancer recurrence was 39.50. Multivariate analysis confirmed that HALP score and some other classic clinicopathological parameters were independently associated with cervical cancer recurrence. Based on the results of multivariate analysis, a nomogram model for predicting cervical cancer recurrence was successfully constructed. The internal and external calibration curves showed that the fitting degree of the model was good, and the C-index (the C-index of the training cohort and the validation cohort were 0.862 and 0.847, respectively) showed that the prediction accuracy of the model proposed in this study was better than other similar models. Conclusion: HALP score may be a novel predictor for predicting the cervical cancer recurrence. Nomogram model based on HALP score and classical clinicopathological parameters can better predict the recurrence of cervical cancer.