In conclusion, we successfully generated a stable 5-Gene model, which could be utilized to predict prognosis of GC patients and would contribute to postoperational treatment and follow-up strategies.

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To investigate the expression pattern, clinical significance and functional roles of microRNA (miR)-615-5p in human esophageal squamous cell carcinoma (ESCC), , quantitative real-time PCR was performed to detect expression levels of miR‑615‑5p in ESCC tissues and cell lines. Associations between miR‑615‑5p expression and various clinicopathological features of ESCC patients were also statistically evaluated. The candidate targets of miR‑615‑5p were identified by integrating bioinformatics miRNA target prediction, western blot analysis and luciferase reporter assay. Moreover, the functions of miR‑615‑5p in ESCC cell migration and invasion were determined using the transfection of miRNA mimics, or co-transfected with miRNA mimics and the expression vector of its target gene. As a result, miR‑615‑5p expression in ESCC tissues and cells were markedly lower than those in non-cancerous esophageal mucosa and human normal esophageal cells, respectively (both P<0.001). miR‑615‑5p downregulation was significantly associated with advanced tumor-node-metastasis stage, positive lymph node metastasis and moderate-poor differentiation. Functionally, the re-expression of miR‑615‑5p suppressed the invasion and migration of ESCC cells in vitro. Interestingly, insulin-like growth factor 2 (IGF2) was identified as a direct target gene of miR‑615‑5p, and the inhibitory effects of miR‑615‑5p in ESCC cell motility were reversed by the restoration of IGF2 expression. In conclusion, miR‑615‑5p downregulation may be an underlying molecular mechanism of development and progression of ESCC, and may function as a potential therapeutic target of this malignancy. Also, we illustrate that the miR‑615‑5p/IGF2 axis may bring important contributions to cell motility of human ESCC.

Glioma causes great harm to people worldwide. Systemic coexpression analysis of this disease could be beneficial for the identification and development of new prognostic and predictive markers in the clinical management of glioma. In this study, we extracted data sets from the Gene Expression Omnibus data set by using "glioma" as the keyword. Then, a coexpression module was constructed with the help of Weighted Gene Coexpression Network Analysis software. Besides, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on the genes in these modules. As a result, the critical modules and target genes were identified. Eight coexpression modules were constructed using the 4,000 genes with a high expression value of the total 141 glioma samples. The result of the analysis of the interaction among these modules showed that there was a high scale independence degree among them. The GO and KEGG enrichment analyses showed that there was a significant difference in the enriched terms and degree among these eight modules, and module 5 was identified as the most important module. Besides, the pathways it was enriched in, hsa04510: Focal adhesion and hsa04610: Complement and coagulation cascades, were determined as the most important pathways. In summary, module 5 and the pathways it was enriched in, hsa04510: Focal adhesion and has 04610: Complement and coagulation cascades, have the potential to serve as biomarkers for patients with glioma.