Bioinformatics reveals the potential mechanisms and biomarkers of necroptosis in neuroblastoma

0Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Background: Neuroblastoma (NB) is a malignant tumor primarily found in children, presenting significant challenges in its development and prognosis. The role of necroptosis in the pathogenesis of NB has been acknowledged as crucial for treatment. This study aimed to investigate the key genes and functional pathways associated with necroptosis, as well as immune infiltration analysis, in NB. Furthermore, we aimed to evaluate the diagnostic significance of these genes for prognostic assessment and explore their potential immunological characteristics. Methods: The NB dataset (GSE19274, GSE73517, and GSE85047) was obtained from the Gene Expression Omnibus (GEO) database, and genes associated with necroptosis were collected from GeneCards and previous literature. First, we conducted differential expression analysis and performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). We employed gene set enrichment analysis (GSEA) to identify overlapping enriched functional pathways from the NB dataset. In addition, we constructed a protein-protein interaction (PPI) network, predicting relevant microRNAs (miRNAs) and transcription factors (TFs), as well as their corresponding drug predictions. Furthermore, the diagnostic value was assessed using receiver operating characteristic (ROC) curves. Finally, an immune infiltration analysis was performed. Results: We identified six necroptosis-related differentially expressed genes (NRDEGs) closely associated with necroptosis in NB. They were enriched in Tuberculosis, Apoptosis-multiple species, Salmonella infection, legionellosis, and platinum drug resistance. GSEA and PPI network analyses, along with mRNA-drug interaction network, revealed 38 potential drugs corresponding to BIRC2, CAMK2G, CASP3, and IL8. ROC curve analysis showed that in GSE19274, FLOT2 with area under the ROC curve (AUC) of 0.850 and DAPK1 with AUC of 0.789. Conclusions: Our study elucidates the key genes and functional pathways associated with necroptosis in NB, offering valuable insights to enhance our comprehension of the pathogenesis of NB, and improve prognosis assessment.

Cite

CITATION STYLE

APA

Gao, B., Yan, S., Xie, W., & Shao, G. (2024). Bioinformatics reveals the potential mechanisms and biomarkers of necroptosis in neuroblastoma. Translational Cancer Research, 13(7), 3599–3619. https://doi.org/10.21037/tcr-24-14

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free