Screening and evaluation of specific blood MiRNAs as potential biomarkers in diagnostics of gastric Cancer.

To provide a novel direction for the diagnosis of gastric cancer (GC). The differentially expressed blood microRNAs (miRNAs) in gastric carcinoma were screened through SangerBox using the datasets GSE113486, GSE112264, and GSE113740. The miRNA-target genes prediction, conduct Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were performed with the Database for Annotation, Visualization and Integrated Discovery (DAVID) 6.8. STRING analysis was further investigated with Cytoscape. The correlations among the expression levels of key miRNAs and prognosis/diagnostic value in GC patients were determined by survival prognosis and Receiver Operating Characteristic (ROC) curve analysis. Quantitative Reverse Transcription Polymerase Chain Reaction (RT-qPCR) was employed to detect the different expression levels of key miRNAs in human blood samples. In the process, the influence of Helicobacter pylori (H. pylori) infection on expression levels of miRNAs was analyzed with Gene Expression Omnibus 2R (GEO2R) in dataset GSE108307. To evaluate these findings, the expression level of Cytotoxin-associated gene A (CagA), along with clinical markers used in the help of GC pathologic diagnosis, were measured and compared with the key miRNAs obtained in this study. The bioinformatics analysis identified five crucial blood miRNAs, including hsa-miR-124-3p, hsa-miR-125a-3p, hsa-miR-29b-3p, hsa-miR-4276, and hsa-miR-575. The detection in human blood samples combined with cross-analysis involving H. pylori infection, the expression levels of CagA and clinical markers underscored the significance and effectiveness of these specific miRNAs in early diagnosis and monitoring of gastric carcinoma. This study identified five potential blood miRNA biomarkers for GC through bioinformatics analysis coupled with detection in human blood samples, thus providing new possibilities for important biomarkers related to diagnosis and prognosis of GC.