Neuroblastoma (NB), a common and highly lethal malignant disease in pediatrics, still lacks an effective therapeutic approach that addresses all conditions. Immunogenic Cell Death (ICD) plays a crucial role in tumor cell death and triggers a potent anti-tumor immune response. In this study, we report an ICD-related index (ICDR-Index) in NB through various machine learning methodologies, utilizing bulk transcriptome data from 1244 NB samples and 16 scRNA-seq datasets. Our results showed that the ICDR-Index could accurately identify different risk subtypes of patients with NB and provide predictive value for prognosis. Importantly, we found that high-risk patients with NB exhibited significantly poor overall survival (OS) rates, adverse clinical phenotypes, poor immune cell infiltration, and low sensitivity to immunotherapy. Furthermore, we identified ELAVL3 as a key gene within the ICDR-Index, where high expression levels were associated with malignancy and poor OS in NB. Additionally, targeted silencing of ELAVL3 down-regulated MYCN gene expression and reduced the malignancy of NB cells. Notably, the si-ELAVL3-transfected NB cells enhanced the anti-tumor activity of NK cells. Collectively, this study offers avenues for predicting the risk stratification of patients with NB and reveals a potential mechanism by which ELAVL3 regulates NB cell death.
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