Immune-Oncology Targets and Therapeutic Response of Cell Pyroptosis-Related Genes with Prognostic Implications in Neuroblastoma

Abstract

Abstract Objective Construction of a NB prognostic model based on pyroptosis-related genes (PRGs) to improve individualized management of NB patients. Methods The GEO-NB cohort from the Gene Expression Omnibus (GEO) database was obtained and randomized into training and test groups, and finally 498 cases were included for analysis. The model was constructed using the training set, and the test set data were used as the validation set to screen for prognostically significant variables using the Log-rank test, and then the optimal multigene prognostic model was built using LASSO-Cox regression analysis. The accuracy of the prognostic model was assessed using ROC curves, column plots, and calibration curves. Results A prognostic model was first developed with the training set: the risk score formula was (-0.30 × GSDMB) + (-0.46 × IL18) + (-0.21 × NLRP3) - (0.56 × AIM2). Patients were categorized into high- and low-risk groups based on the median risk score value. Survival analysis showed that NB patients in the high-risk group had a significantly lower survival rate than those in the low-risk group (P < 0.001). The area under curve (AUC) of the time-dependent ROC curve predicting 5-, 7.5-, and 10-year survival was 0.843, 0.802, and 0.797, respectively. In the GEO test cohort, patients in the high-risk group had worse prognostic patients compared with those in the low-risk group (P=0.035). The calibration curve of the alignment diagram show that the alignment diagram has good clinical value. Conclusion A prognostic model for predicting survival in NB patients was constructed based on PRGs, and the accuracy of the model was validated in an overall cohort and test cohort.