Zhang (2021) Bioinformatics analysis reveals the landscape of immune cell infiltration and immune-related pathways participating in the progression of carotid atherosclerotic plaques,

Background: Vulvar carcinoma is a rare gynecological malignancy. The most commonly used staging system for vulvar cancer is the 2009 International Federation of Gynecology and Obstetrics (FIGO) staging system. Nevertheless, it does not incorporate many indispensable prognostic parameters, which prominently influence vulvar cancer patient survival. Thus, the development of a prediction model for evaluating survival prognosis in postoperative vulvar squamous cell cancer patients is of vital importance. Methods: Data from 2,166 patients with pathologically confirmed diagnosis of vulvar squamous cell carcinoma from 2004 to 2015 were acquired from the Surveillance, Epidemiology, and End Results (SEER) database. Thirty percent of the patients were randomly assigned to the validation group, and the remainder were used to develop the nomogram. Parameters that significantly correlated with overall survival (OS) were used to create the nomogram. Concordance index (C-index), calibration curve, and decision curve analysis (DCA) were used to assess the predictive accuracy and discriminability of the nomogram model. Additionally, the C-index and DCA of the nomogram and the FIGO staging system were compared. Results: Following multivariate analysis of the training cohort, independent factors for OS, including race, age at diagnosis, marital status, FIGO stage, tumor diameter, and lymph node ratio (LNR), were included in the nomogram model. The calibration curve indicated a high correlation between the nomogram-predicted and observed survival probability. The C-index of the nomogram in the training cohort was 0.772 (95% CI:0.752-0.792), statistically superior to the C-index value of the FIGO staging system (0.676, 95% CI: 0.654-0.698). In DCA, compared to the FIGO staging system, this nomogram showed a greater net benefit and a wider range of threshold probability. Results were verified by an internal validation cohort.Conclusions: Our nomogram, based on LNR, showed superior prognostic predictive accuracy compared with the FIGO staging system for predicting OS in postoperative vulvar squamous cell carcinoma patients.

Purpose: Cuproptosis, a form of copper-induced cell death, can be a promising therapeutic target for refractory cancers. Hence, we conducted this research to explore the association between cuproptosis and prognosis in cervical cancer (CC).Methods: For constructing a prognostic signature based on cuproptosis-related genes from TCGA database, the least absolute shrinkage and selection operator Cox regression was utilized. The GSE44001 cohort was utilized for validation.Results: A total of nine cuproptosis-related genes showed distinct expression in CC and normal samples in TCGA-GTEx cohort. Two risk groups were identified based on a seven-gene signature. A significant decrease in overall survival was observed in the high-risk group (p < 0.001). The risk score (HR = 2.77, 95% CI = 1.58–4.86) was an autocephalous predictor with a better predictive ability than the clinical stage. Functional analysis indicated that immune activities were suppressed more in the high-risk group than in the low-risk group. A total of 11 candidate compounds targeting the signature were identified.Conclusion: A total of seven cuproptosis-related gene signatures were constructed to predict prognosis and propose a new therapeutic target for patients with CC.