Background: Metastatic cervical cancer (mCEC) is the end stage of cervical cancer. This study aimed to establish and validate a nomogram to predict the overall survival (OS) of mCEC patients.Methods: We investigated the Surveillance, Epidemiology, and End Results (SEER) database for mCEC patients diagnosed between 2010 and 2014. Univariate and multivariable Cox analyses was performed to select the clinically important predictors of OS when developing the nomogram. The performance of nomogram was validated with Harrell's concordance index (C-index), calibration curves, receiver operating characteristic curve (ROC), and decision curve analysis (DCA).Results: One thousand two hundred and fifty-two mCEC patients were included and were divided into training (n = 880) and independent validation (n = 372) cohorts. Age, race, pathological type, histology grade, radiotherapy, and chemotherapy were independent predictors of OS and used to develop the nomogram for predicting 1- and 3-year OS. This nomogram had a C-index of 0.753 (95% confidence interval [CI]: 0.780–0.726) and 0.751 (95% CI: 0.794–0.708) in the training and the validation cohorts, respectively. Internal and external calibration curves indicated satisfactory agreement between nomogram prediction and actual survival, and DCA indicated its clinical usefulness. Furthermore, a risk stratification system was established that was able to accurately stratify mCEC patients into three risk subgroups with significantly different prognosis.Conclusions: We constructed the first nomogram and corresponding risk classification system to predict the OS of mCEC patients. These tools showed satisfactory accuracy, and clinical utility, and could aid in patient counseling and individualized clinical decision-making.

Background Marital status serves as an independent prognostic factor for survival in a variety of cancers. However, its prognostic impact on soft tissue sarcoma (STS) has not yet been established. Objective To investigate the impact of marital status on survival outcomes among STS patients. Methods A total of 18 013 STS patients diagnosed between 2004 and 2015 were extracted from Surveillance, Epidemiology, and End Results (SEER) database. The marital status was classified into married, divorced, widowed, and single. Kaplan‐Meier analysis and multivariate Cox proportional hazards regression analysis were conducted to establish the impact of marital status on the overall survival (OS) and cancer‐specific survival (CSS). Subgroup analyses were conducted based on age, SEER historic stage and surgery condition. Propensity score matching (PSM) was used to perform a 1:1 matched‐pair analysis to minimize the group differences caused by covariates. Results Married patients enjoyed better 5‐year overall survival (OS) and 5‐year cancer‐specific survival (CSS), compared with patients who were divorced, widowed, and single, respectively. Multivariate Cox proportional hazards regression analysis revealed that marital status was an independent prognostic and protective factor for survival among STS patients, and unmarried status was associated with higher mortality hazards for both OS and CSS. Additionally, widowed individuals had the highest risks of overall and cancer‐specific mortality compared to other unmarried groups. In the subgroup analyses, similar associations were also found. Furthermore, marital status still remained an independent prognostic and protective factor for both OS and CSS even in 1:1 matched‐pair analysis. Conclusions Marital status was an independent prognostic and protective factor for survival for STS patients. Widowed patients suffered the highest death risks among the unmarried groups.

BackgroundAberrant activation of Wnt/β-catenin has been shown to promote ovarian cancer proliferation and chemoresistance. Pyrvinium, an FDA-approved anthelmintic drug, has been identified as a potent Wnt inhibitor. Pyrvinium may sensitize ovarian cancer cells to chemotherapy.Material/MethodsThe effect of pyrvinium alone and its combination with paclitaxel in ovarian cancer was investigated using an in vitro culture system and in vivo xenograft models. The mechanisms of its action were also analyzed, focusing on the Wnt/β-catenin pathway.ResultsPyrvinium inhibited growth and induced apoptosis of paclitaxel- and cisplatin-resistant epithelial ovarian cancer cell lines A2278/PTX and SK-OV-3. Its combination with paclitaxel was synergistic in targeting ovarian cancer cells in vitro. In 3 independent ovarian xenograft mouse models, pyrvinium alone inhibited tumor growth. More importantly, we observed significant inhibition of tumor growth throughout the treatment when using pyrvinium and paclitaxel combined. Mechanistically, pyrvinium increased the Wnt-negative regulator axin and decreased the β-catenin levels in ovarian cancer cells. In addition, pyrvinium suppressed Wnt/β-catenin-mediated transcription, as shown by the decreased mRNA levels of MYC, cyclin D, and BCL-9. In contrast, the inhibitory effects of pyrvinium were reversed by β-catenin stabilization or overexpression, demonstrating that pyrvinium acted on ovarian cancer cells via targeting the Wnt/β-catenin signaling pathway.ConclusionsWe demonstrated that the anthelmintic drug pyrvinium targets ovarian cancer cells through suppressing Wnt/β-catenin signaling. Our work highlights the therapeutic value of inhibiting Wnt/β-catenin in ovarian cancer.

Background Gastric cancer (GC) is the fourth most frequently diagnosed malignancy and the second leading cause of cancer-associated mortality worldwide. The tumor microenvironment, especially tumor-infiltrating immune cells (TIICs), exhibits crucial roles both in promoting and inhibiting cancer growth. The aim of the present study was to evaluate the landscape of TIICs and develop a prognostic nomogram in GC. Materials and Methods A gene expression profile obtained from a dataset from The Cancer Genome Atlas (TCGA) was used to quantify the proportion of 22 TIICs in GC by the CIBERSORT algorithm. LASSO regression analysis and multivariate Cox regression were applied to select the best survival-related TIICs and develop an immunoscore formula. Based on the immunoscore and clinical information, a prognostic nomogram was built, and the predictive accuracy of it was evaluated by the area under the curve (AUC) of the receiver operating characteristic curve (ROC) and the calibration plot. Furthermore, the nomogram was validated by data from the International Cancer Genome Consortium (ICGC) dataset. Results In the GC samples, macrophages (25.3%), resting memory CD4 T cells (16.2%) and CD8 T cells (9.7%) were the most abundant among 22 TIICs. Seven TIICs were filtered out and used to develop an immunoscore formula. The AUC of the prognostic nomogram in the TCGA set was 0.772, similar to that in the ICGC set (0.730) and whole set (0.748), and significantly superior to that of TNM staging alone (0.591). The calibration plot demonstrated an outstanding consistency between the prediction and actual observation. Survival analysis revealed that patients with GC in the high-immunoscore group exhibited a poor clinical outcome. The result of multivariate analysis revealed that the immunoscore was an independent prognostic factor. Discussion The immunoscore could be used to reinforce the clinical outcome prediction ability of the TNM staging system and provide a convenient tool for risk assessment and treatment selection for patients with GC.