Background:Due to the extremely high mortality rate of children with high-risk Neuroblastoma (NB), there is an urgent need for new indicators to further classify children in the high-risk group for more precise treatment. The purpose of our research is to explore the immune-related genes in NB in the high-risk group, and to further identify and develop a prognostic nomogram based on immune IRG signatures. Methods:Through bioinformatics analysis to explore the abnormal expression of immune-related genes in the high-risk group. Cox regression and the least absolute shrinkage and selection operator (LASSO) analysis were conducted to identify the immune and overall survival (OS) related mRNA. The accuracy of the risk score is evaluated by Kaplan-Meier method and receiver operating characteristics (ROC) analysis, which is used to build a nomogram in combination with other clinical characteristics.. Quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to detect the accuracy of our results. Results:A total of 127 common differentially expressed immune genes were found between the high-risk group and the non-high-risk group of the two data sets. Four immune-related genes (IRG) related to prognosis were identified and a risk score was established. Kaplan–Meier survival analysis and time-dependent ROC analysis showed that the 4-IRG risk score has satisfactory predictive potential and achieved consistency in the verification of external data sets. Subsequently, the risk score combined with clinical characteristics draws a nomogram. The reliability of the results was verified on 29 cases of NB tissues by qRT-PCR. Conclusions:Overall, we have developed a powerful multi-gene classifier that can effectively classify NB patients into low- and high-risk groups with poor prognosis, and draw a nomogram for children in the high-risk group. This feature can help select high-risk patients who need more aggressive adjuvant target therapy or immunotherapy.
The study of target genes for the spontaneous regression phenomenon of neuroblastoma (NB) is still unclear. Common differentially expressed genes (DEGs) were identified by differential expression analysis in both public databases for the stage 4 death group and stage 4S survival group. The DEGs were ranked by constructing protein-protein interaction (PPI) network as well as calculating betweenness centrality (BC) values, and the relationship with NB prognosis was determined by performing univariate analysis, multifactor analysis, and lasso regression analysis on the top 10 genes and possibly correlated with spontaneous regression of NB. We identified a total of 173 DEGs, including 143 upregulated genes and 30 downregulated genes. PPI network showed a rich interaction between DEGs. We ranked the DEGs by calculating BC values and showed the top 10 genes, followed by univariate and multifactorial analyses, which showed that GRIA2, NTRK1, SCN9A, SLC18A2, CNR1, PIK3R1, and DGKB were associated with good prognosis, and CNR1 was the most closely associated with prognosis among them. By lasso regression analysis, we constructed a four-gene risk score formula. We drew a nomogram to use in clinical work and two newly identified genes associated with good prognosis in NB: CNR1 and GIRA2.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.