Qincheng Liu1,2, Wei Zhang1,2, Zhenqian Wu3, Haijun Liu1,2, Huiqiong Hu1,2, Huisen Shi1,2, Shaohua Li1,2, Xueli Zhang1,2. 1. Department of General Surgery, Shanghai Fengxian Central Hospital (Affiliated Fengxian Hospital to Southern Medical University), The Third School of Clinical Medicine, Southern Medical University, Shanghai, China. 2. The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China. 3. The Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
Abstract
OBJECTIVES: Circular RNAs (circRNAs) can interact with microRNAs (miRNAs) to regulate gene expression in cancer cells. However, the roles of competitive endogenous RNA (ceRNA) networks consisting of differentially expressed circRNAs (DECs), miRNAs, and messenger RNAs (mRNAs) in stomach adenocarcinoma (STAD) remain unclear. This study was performed to explore novel regulatory networks in STAD. METHODS: The circRNA expression profiles, as well as miRNA and mRNA sequence data of STAD, were retrieved from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), respectively. Candidates were identified to construct a network through a comprehensive bioinformatics strategy. The expression of hub-genes identified by protein-protein interactions (PPI) was validated by quantitative reverse transcription (RT) polymerase chain reaction. RESULTS: A total of 51 DECs were identified in the GSE83521 and GSE89143 datasets of GEO. A total of 11 448 differentially expressed mRNAs (DEMs) and 458 differentially expressed miRNAs (DEMIs) were obtained by RNA sequencing of TCGA-STAD. Prediction by using five online databases (Cancer-Specific CircRNA, CircInteractome, miRTarBase, miRDB, and TargetScan) resulted in the selection of 6 DECs, 6 DEMIs, and 36 DEMs to establish a circRNA-miRNA-mRNA regulatory network based on the interactions of circRNA-miRNA and miRNA-mRNA. Through PPI analysis, four hub-genes (COL10A1, COL5A2, COL4A1, and COL3A1) were discovered. Moreover, overexpressions of COL10A1, COL5A1, and COL4A1 were associated with a poor overall survival rate of patients with STAD. On the basis of TNM staging, we found that the expressions of COL10A1, COL5A2, and COL3A1 in T2, T3, and T4 was significantly higher than in T1. Hub-genes expressions were validated in STAD tissues and cell lines. CONCLUSIONS: Our study provides a novel perspective on the regulatory mechanism of STAD involving ceRNAs including DECs, DEMIs, and DEMs.
OBJECTIVES: Circular RNAs (circRNAs) can interact with microRNAs (miRNAs) to regulate gene expression in cancer cells. However, the roles of competitive endogenous RNA (ceRNA) networks consisting of differentially expressed circRNAs (DECs), miRNAs, and messenger RNAs (mRNAs) in stomach adenocarcinoma (STAD) remain unclear. This study was performed to explore novel regulatory networks in STAD. METHODS: The circRNA expression profiles, as well as miRNA and mRNA sequence data of STAD, were retrieved from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), respectively. Candidates were identified to construct a network through a comprehensive bioinformatics strategy. The expression of hub-genes identified by protein-protein interactions (PPI) was validated by quantitative reverse transcription (RT) polymerase chain reaction. RESULTS: A total of 51 DECs were identified in the GSE83521 and GSE89143 datasets of GEO. A total of 11 448 differentially expressed mRNAs (DEMs) and 458 differentially expressed miRNAs (DEMIs) were obtained by RNA sequencing of TCGA-STAD. Prediction by using five online databases (Cancer-Specific CircRNA, CircInteractome, miRTarBase, miRDB, and TargetScan) resulted in the selection of 6 DECs, 6 DEMIs, and 36 DEMs to establish a circRNA-miRNA-mRNA regulatory network based on the interactions of circRNA-miRNA and miRNA-mRNA. Through PPI analysis, four hub-genes (COL10A1, COL5A2, COL4A1, and COL3A1) were discovered. Moreover, overexpressions of COL10A1, COL5A1, and COL4A1 were associated with a poor overall survival rate of patients with STAD. On the basis of TNM staging, we found that the expressions of COL10A1, COL5A2, and COL3A1 in T2, T3, and T4 was significantly higher than in T1. Hub-genes expressions were validated in STAD tissues and cell lines. CONCLUSIONS: Our study provides a novel perspective on the regulatory mechanism of STAD involving ceRNAs including DECs, DEMIs, and DEMs.