The potential mechanisms of neuroblastoma in children based on bioinformatics big data

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Abstract

Background: In recent years, miRNAs have become a research hotspot, which is related to the occurrence and development of a variety of malignant tumors, but there are few studies in neuroblastoma. In this study, the differentially expressed microRNAs (miRNAs) in neuroblastoma were identified and analyzed using bioinformatics, and their biological functions and related signaling pathways were examined. Methods: The neuroblastoma miRNA chip GSE121513 was obtained from the Gene Expression Omnibus (GEO) database and the data of 95 neuroblastoma samples and normal fetal adrenal neuroblastoma samples were analyzed to screen the differential miRNAs. The target genes of the differentially expressed miRNAs were predicted using |log fold change (FC)| ≥4. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were performed to construct a protein-protein interaction network and identify the core target genes. Results: A total of 91 differentially expressed miRNAs were identified (P<0.05, |logFC| ≥1), including 52 upregulated and 39 downregulated miRNAs. The target genes of the differential miRNAs (P<0.05, |logFC| ≥4) were pretested, and 602 target genes were obtained. Functional analysis showed that these genes were mainly located in the extracellular matrix region of proteins, and were involved in the negative regulation of cytoplasmic translation, mRNA 3'-untranslated region (UTR) binding, and binding to nucleic acid to inhibit the activity of translation factors. They were also involved in RNA degradation, adhesion pathways, and the phosphatidylinositol-3-kinase (PI3K)-Akt signaling pathway. Ten key target genes were identified via protein interaction network screening. Conclusions: The differential miRNAs may be related to the occurrence of neuroblastoma were screened.

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Chen, Z. F., Wu, L. Z., Chen, Z. T., Su, L. J., & Fu, C. J. (2022). The potential mechanisms of neuroblastoma in children based on bioinformatics big data. Translational Pediatrics, 11(12), 1908–1919. https://doi.org/10.21037/tp-22-504

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