Objective: To analyze the differential miRNAs and target genes of normal striated muscle and rhabdomyosarcoma (RMS) tissues by using bioinformatics methods

so as to provide new ideas for RMS study. Methods: GEO2R was used to analyze the differential miRNAs of RMS. Sangerbox was used to draw volcanic maps. TargetScan

miRDB and miRwalk were used to predict the intersection of target genes. Enrichr was used to analyze GO enrichment analysis and KEGG signaling pathway of target genes. Cytoscape combined survival analysis was used to screen the hub gene and its molecular regulatory network with miRNAs. Results: According to GEO2R analysis

2 549 differential miRNAs were obtained

of which 1 318 and 1 231 miRNAs were up-regulated and down-regulated

respectively. According to|log2FC|>1.5 and P<0.05

six differential miRNAs (up-regualted: miR-410-3p

miR-381-3p

miR-483-3p and miR-376a-3p; down-regulated: miR-29c-3p and miR-145-5p) were screened. TargetScan

miRDB and miR-walk predicted the target genes of the six differential miRNAs

and a total of 1 262 target genes were obtained from the Veen plot. GO enrichment and KEGG signal pathway analysis of differential miRNAs-target genes revealed that enrichment was in the regulation of RNA polymeraseⅡand regulated the signal pathway of stem cell pluripotency and the Hippo signaling pathway. After cytoscape analysis screening top10 hub genes

it combined with survival curve analysis showed that high expression of FBXL3 and low expression of SPSB4

VHL

SMAD4

NRAS and KRAS had a better prognosis. Conclusion: Utilizing bioinformatics to analyze differential miRNAs-target genes of normal striated muscle and RMS

miR-145-5p (SPSB4

FBXL3

SMAD4

NRAS)

miR-29c-3p (VHL) and miR-381-3p (KRAS) are screened

which can provide potential molecular targets for the study of RMS.