CircRNAs: Insights into Gastric Cancer

Identification and validation of key genes in gastric cancer: insights from in silico analysis, clinical samples, and functional assays

INTRODUCTION

The underlying mechanisms of gastric cancer (GC) remain unknown. Therefore, in this study, we employed a comprehensive approach, combining computational and experimental methods, to identify potential key genes and unveil the underlying pathogenesis and prognosis of GC.

METHODS

Gene expression profiles from GEO databases (GSE118916, GSE79973, and GSE29272) were analyzed to identify DEGs between GC and normal tissues. A PPI network was constructed using STRING and Cytoscape, followed by hub gene identification with CytoHubba. Investigations included expression and promoter methylation analysis, survival modeling, mutational and miRNA analysis, gene enrichment, drug prediction, and in vitro assays for cellular behaviors.

RESULTS

A total of 83 DEGs were identified in the three datasets, comprising 41 up-regulated genes and 42 down-regulated genes. Utilizing the degree and MCC methods, we identified four hub genes that were hypomethylated and up-regulated: COL1A1, COL1A2, COL3A1, and FN1. Subsequent validation of their expression and promoter methylation on clinical GC samples through targeted bisulfite sequencing and RT-qPCR analysis further confirmed the hypomethylation and overexpression of these genes in local GC patients. Furthermore, it was observed that these hub genes regulate tumor proliferation and metastasis in in vivo and exhibited mutations in GC patients.

CONCLUSION

We found four potential diagnostic and prognostic biomarkers, including COL1A1, COL1A2, COL3A1, and FN1 that may be involved in the occurrence and progression of GC.

Identification of significant genes associated with prognosis of gastric cancer by bioinformatics analysis

BACKGROUND

Gastric cancer (GC) ranks second in mortality among all malignant diseases worldwide. However, the cause and molecular mechanism underlying gastric cancer are not clear. Here, we used integrated bioinformatics to identify possible key genes and reveal the pathogenesis and prognosis of gastric cancer.

METHODS

The gene expression profiles of GSE118916, GSE79973, and GSE29272 were available from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between GC and normal gastric tissues were screened by R software and Venn diagram software. GO and KEGG pathway enrichment of DEGs was performed using the DAVID database. A protein-protein interaction (PPI) network was established by STRING and visualized using Cytoscape software. Then the influence of hub genes on expression and survival was assessed using TCGA database.

RESULTS

A total of 83 DEGs were found in the three datasets, including 41 up-regulated genes and 42 down-regulated genes. These DEGs were mainly enriched in extracellular matrix organization and cell adhesion. The enriched pathways obtained in the KEGG pathway analysis were extracellular matrix (ECM)-receptor interaction and focal adhesion. A PPI network of DEGs was analyzed using the Molecular Complex Detection (MCODE) app of Cytoscape. Four genes were considered hub genes, including COL5A1, FBN1, SPARC, and LUM. Among them, LUM was found to have a significantly worse prognosis based on TCGA database.

CONCLUSIONS

We screened DEGs associated with GC by integrated bioinformatics analysis and found one potential biomarker that may be involved in the progress of GC. This hub gene may serve as a guide for further molecular biological experiments.

Critical Roles of Circular RNA in Tumor Metastasis via Acting as a Sponge of miRNA/isomiR

Circular RNAs (circRNAs), a class of new endogenous non-coding RNAs (ncRNAs), are closely related to the carcinogenic process and play a critical role in tumor metastasis. CircRNAs can lay the foundation for tumor metastasis via promoting tumor angiogenesis, make tumor cells gain the ability of migration and invasion by regulating epithelial-mesenchymal transition (EMT), interact with immune cells, cytokines, chemokines, and other non-cellular components in the tumor microenvironment, damage the normal immune function or escape the immunosuppressive network, and further promote cell survival and metastasis. Herein, based on the characteristics and biological functions of circRNA, we elaborated on the effect of circRNA via circRNA-associated competing endogenous RNA (ceRNA) network by acting as miRNA/isomiR sponges on tumor angiogenesis, cancer cell migration and invasion, and interaction with the tumor microenvironment (TME), then explored the potential interactions across different RNAs, and finally discussed the potential clinical value and application as a promising biomarker. These results provide a theoretical basis for the further application of metastasis-related circRNAs in cancer treatment. In summary, we briefly summarize the diverse roles of a circRNA-associated ceRNA network in cancer metastasis and the potential clinical application, especially the interaction of circRNA and miRNA/isomiR, which may complicate the RNA regulatory network and which will contribute to a novel insight into circRNA in the future.

Biological and clinical implications of hsa_circ_0086720 in gastric cancer and its clinical application

Background

Circular RNAs (circRNAs) are thought to be vital participants in carcinogenesis and have the characteristics of being stable, specific, and well conserved. However, their clinical significance and application value in gastric cancer (GC) are still poorly understood. Hsa_circ_0086720 was found to be a dysregulated circRNA in GC by microarray screening and was further explored for its clinical significance and application.

Methods

Hsa_circ_0086720 was detected in GC cell lines, tissues, and plasma, and the clinicopathological correlations were investigated. The existence, stability, origin, and change in the plasma hsa_circ_0086720 level were verified in early GC patients. Moreover, receiver operating characteristic and Kaplan–Meier survival curves were constructed to analyze the diagnostic and prognostic values, and bioinformatics analysis was used to identify the potential functions. Finally, risk factors and nomogram predicting were established.

Results

Hsa_circ_0086720 was found to be downregulated in gastric carcinogenesis, and tissue hsa_circ_0086720 was negatively associated with perineural invasion, Borrmann type, disease‐free survival, and overall survival. Hsa_circ_0086720 was stable in circulating plasma and was actively secreted by cells in gastric carcinogenesis. As a biomarker for early GC screening, plasma hsa_circ_0086720 had good sensitivity and specificity, and its stability met the clinical application requirements. Bioinformatics analysis suggested that dysregulated hsa_circ_0086720 has important functions in gastric carcinogenesis. Univariate Cox regression analysis identified factors associated with overall survival time and disease‐free survival time. The nomograms showed good accuracy of predicting survival time.

Conclusion

Hsa_circ_0086720 is a novel biomarker for screening early GC and predicting the prognosis of advanced‐stage patients.