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Objective. In this study, we screened out a type of differentially expressed circular RNA in infantile hemangioma (IH) cells and analyzed the mechanism in the malignant biological behavior of IH. Methods. Based on the GSE98795, GSE100682, and GSE43742 datasets, differential expression analysis of circRNAs, microRNAs, and mRNAs was performed. The relative expression level of RNA was detected by quantitative real-time polymerase chain reaction (qRT-PCR). MTT assay, Transwell, flow cytometry analysis, and western blot were used to study the effects of hsa_circ_0003570, hsa-miR-138-5p, and RGS5 on the proliferation and apoptosis of hemangioma endothelial cells (HEMECs). Results. The hsa_circ_0003570 and RGS5 mRNA were upregulated in HEMECs, but hsa-miR-138-5p was downregulated. Silencing of hsa_circ_0003570 inhibited the proliferation of HEMECs and promoted the apoptosis of HEMECs. The malignant biological behaviors of hsa_circ_0003570 on the proliferation and apoptosis of HEMECs were reversed by hsa-miR-138-5p. Hsa_circ_0003570 acted as the ceRNA of hsa-miR-138-5p and upregulated the expression of RGS5. Silencing of RGS5 inhibited the proliferation, migration, and invasion of HEMECs and promoted apoptosis. Conclusion. Hsa_circ_0003570 promotes IH cell proliferation and inhibits IH cell apoptosis through hsa-miR-138-5p/RGS5 axis.

Background: Gastric cancer (GC) is one of lethal diseases worldwide. Autophagy-associated genes play a crucial role in the cellular processes of GC. Our study aimed to investigate and identify the prognostic potential of autophagy-associated genes signature in GC. Methods: RNA-seq and clinical information of GC and normal controls were downloaded from The Cancer Genome Atlas (TCGA) database. Then, the Wilcoxon signed-rank test was used to pick out the differentially expressed autophagy-associated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to investigate the potential roles and mechanisms of autophagy-associated genes in GC. Cox proportional hazard regression analysis and Lasso regression analysis were carried out to identify the overall survival (OS) related autophagy-associated genes, which were then collected to construct a predictive model. Kaplan-Meier method and receiver operating characteristic (ROC) curve were utilized to validate the accuracy of this model. Finally, a clinical nomogram was established by combining the clinical factors and autophagy-associated genes signature. Results: A total of 28 differentially expressed autophagy-associated genes were identified. GO and KEGG analyses revealed that several important cellular processes and signaling pathways were correlated with these genes. Through Cox regression and Lasso regression analyses, we identified 4 OS-related autophagy-associated genes (GRID2, ATG4D, GABARAPL2, and CXCR4) and constructed a prognosis prediction model. GC Patients with high-risk had a worse OS than those in low-risk group (5-year OS, 27.7% vs 38.3%; P=9.524e-07). The area under the ROC curve (AUC) of the prediction model was 0.67. The nomogram was demonstrated to perform better for predicting 3-year and 5-year survival possibility for GC patients with a concordance index (C-index) of 0.70 (95% CI: 0.65-0.72). The calibration curves also presented good concordance between nomogram-predicted survival and actual survival. Conclusions: We constructed and evaluated a survival model based on the autophagy-associated genes for GC patients, which may improve the prognosis prediction in GC.