Background To explore the factors that affect the prognosis of overall survival (OS) and cancer-specific survival (CSS) of patients with stage IIIC1 cervical cancer and establish nomogram models to predict this prognosis. Methods Data from patients in the Surveil-lance, Epidemiology, and End Results (SEER) programme meeting the inclusion criteria were classified into a training group, and validation data were obtained from the First Affiliated Hospital of Anhui Medical University from 2010 to 2019. The incidence, Kaplan-Meier curves, OS and CSS of patients with stage IIIC1 cervical cancer in the training group were evaluated. Nomograms were established according to the results of univariate and multivariate Cox regression models. Harrell’s C-index, calibration plots, receiver operating characteristic (ROC) curves and decision-curve analysis (DCA) were calculated to validate the prediction models. Results The incidence of pelvic lymph node metastasis, a high-risk factor for the prognosis of cervical cancer, decreased slightly over time. Eight independent prognostic variables were identified for OS, including age, race, marriage status, histology, extension range, tumour size, radiotherapy and surgery, but only seven were identified for CSS, with marriage status excluded. Nomograms of OS and CSS were established based on the results. The C-indexes for the nomograms of OS and CSS were 0.687 and 0.692, respectively, using random sampling of SEER data sets and 0.701 and 0.735, respectively, using random sampling of external data sets. The AUCs for the nomogram of OS were 0.708 and 0.705 for the SEER data sets and 0.750 and 0.750 for the external data sets, respectively. In addition, AUCs of 0.707 and 0.709 were obtained for the nomogram of CSS when validated using SEER data sets, and 0.788 and 0.785 when validated using external data sets. Calibration plots for the nomograms were almost identical to the actual observations. The DCA also indicated the value of the two models. Conclusions Eight independent prognostic variables were identified for OS. The same factors predicted CSS, with the exception of the marriage status. Both OS and CSS nomograms had good predictive and clinical application value after validation. Notably, tumour size had the largest contribution to the OS and CSS nomograms.

Accumulating evidence has demonstrated that long noncoding RNAs (lncRNAs) exert essential biological functions in modulating the progression of endometrial carcinoma (EC). HOX transcript antisense intergenetic RNA (HOTAIR) has been widely recognized as a crucial mediator in various tumors, including EC. However, the specific molecular mechanism of HOTAIR in the development of EC remains to be further explored. In the present study, we demonstrated that HOTAIR was significantly upregulated in EC tissues; this was negatively correlated with PTEN but positively correlated with phosphatidylinositol 3-kinase (PI3K) and Akt. Overexpression of HOTAIR promoted proliferation and inhibited apoptosis of EC cells, similar to PTEN knockdown. Additionally, RNA pulldown demonstrated the direct binding relationship between HOTAIR and PTEN. Furthermore, HOTAIR activated the PI3K/Akt pathway to promote EC progression by suppressing PTEN in vivo. Taking these results together, we revealed that high expression of HOTAIR promoted cell proliferation and inhibited apoptosis through activating the PI3K/Akt pathway via binding to PTEN, which might provide a prognostic marker and therapeutic target of EC.

BackgroundThe aim of this study is to determine pathological factors that increase the risk of LNM and indicate poor survival of patients diagnosed with endometrial cancer and treated with surgical staging.MethodBetween January 2010 and November 2018, we enrolled 874 eligible patients who received staging surgery in the First Affiliated Hospital of Anhui Medical University. The roles of prognostic risk factors, such as age, histological subtype, tumor grade, myometrial infiltration, tumor diameter, cervical infiltration, lymphopoiesis space invasion (LVSI), CA125, and ascites, were evaluated. Multivariable logistic regression models were used to identify the predictors of LNM. Kaplan–Meier and COX regression models were utilized to study the overall survival.ResultsMultivariable regression analysis confirmed cervical stromal invasion (OR 3.412, 95% CI 1.631–7.141; P < 0.01), LVSI (OR 2.542, 95% CI 1.061–6.004; P = 0.04) and ovarian metastasis (OR 6.236, 95% CI 1.561–24.904; P = 0.01) as significant predictors of nodal dissemination. Furthermore, pathological pattern (P = 0.03), myometrial invasion (OR 2.70, 95% CI 1.139–6.40; P = 0.01), and lymph node metastasis (OR 9.675, 95% CI 3.708–25.245; P < 0.01) were independent predictors of decreased overall survival.ConclusionsCervical invasion, lymphopoiesis space invasion, and ovarian metastasis significantly convey the risk of LNM. Pathological type, myometrial invasion, and lymph node metastasis are all important predictors of survival and should be scheduled for completion when possible in the surgical staging procedure.

BackgroundThe purpose of this study is to explore the factors that affect the prognosis of overall survival (OS) and cancer special survival (CSS) in cervical cancer with stage IIIC1 and establish nomogram models to predict this prognosis.MethodsData from The Surveil-lance, Epidemiology, and End Results (SEER) Program meeting the inclusion criterions were classified into training group, and data of validation were obtained from the First Affiliated Hospital of Anhui Medical University from 2010 to 2019. The incidence, Kaplan‐Meier curves, OS and CSS of stage IIIC1 were evaluated according to the training group. Nomograms were established according to the results of univariate and multivariate Cox regression models. Harrell’s C-index and receiver operating characteristic curve (ROC) were calculated to measure the accuracy of the prediction models. Calibration plots show the relationship between the predicted probability and the actual outcome. Decision-curve analysis (DCA) was applied to evaluate the clinical applicability of the constructed nomogram.ResultsThe incidence of pelvic lymph node metastasis, a high-risk factor for prognosis in cervical cancer, decreased slightly over time. There are eight independent prognostic variables for OS, including age, race, histology, differentiation, extension range, tumor size, radiation recode and surgery, but seven for CSS with age excluded. Nomograms of OS and CSS were established based on the results. The C-index for the nomograms of OS and CSS were 0.692, 0.689 respectively when random sampling of SEER data sets, and 0.706, 0.737 respectively when random sampling of external data sets. AUCs for the nomogram of OS were 0.648, 0.644 respectively, and 0.683, 0.675 for the nomogram of CSS. Calibration plots for the nomograms were almost identical to the actual observations. The DCA also proved the value of the two models.ConclusionAge, race, histology, differentiation, extension range, tumor size, radiation recode and surgery were all independent prognosis factors for OS. Only age excepts in CSS. OS and CSS nomograms were established in our study based on the result of multivariate Cox proportional hazard regression, and both own good predictive and clinical application value after validation.