Identification and verification of international neuroblastoma staging system (INSS) stage-related genes as potential biomarkers for neuroblastoma prognostic models.

BACKGROUND: Neuroblastoma (NB), one of the most common malignant extracranial solid tumors in children, is highly invasive and lethal with limited treatment efficacy. This study aimed to establish a prognostic model of advanced-stage NB. METHODS: Differentially expressed genes were screened and validated using two training datasets and one validation dataset from the Therapeutically Applicable Research to Generate Effective Treatments and Gene Expression Omnibus databases. Protein-protein interaction networks were developed using the MCode plug-in, and the top three key clusters were used to produce candidate genes. We performed gene set enrichment analysis (GSEA), gene ontology analysis (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, immune cell infiltration, and drug sensitivity analysis to further understand the functions of these candidate genes. Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curves were used to check their prognosis value. Real-time quantitative polymerase chain reaction (qPCR), Western blot (WB), and immunohistochemistry (IHC) were employed to verify the mRNA and protein levels in clinical samples. RESULTS: A total of 699 differentially expressed genes were identified, including 294 upregulated and 405 downregulated genes. CNR1, PRKACB, CDKN3, and PCLAF were found to significantly affect the overall survival and event-free survival of neuroblastoma patients and were positively correlated with the INSS advanced stages. The functional analysis of these four genes revealed their cancer-promoting effects and correlations with immune-inflammatory, cell cycle, and p53 signaling pathways. After stratifying patients using the established model containing the above four genes, significantly different patterns were observed in terms of infiltrating immune cell proportion, drug sensitivity, and the expression of immune checkpoints. Finally, both the mRNA and protein expression verification assays demonstrated that the CDKN3 and PCLAF were upregulated, while the PRKACB was downregulated in advanced-stage neuroblastoma tissue samples. CONCLUSION: The model containing CNR1, PRKACB, CDKN3, and PCLAF can serve as a new prognostic biomarker for predicting the prognosis of patients with neuroblastoma. Findings on immune cell infiltration and immune checkpoints provide novel insights for the immunotherapy of neuroblastoma.