R Li1, W J Jiang2, S L Jin1, R H Zhao1, X G Cao3, H Zong1. 1. Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China. 2. Department of Oncology, The Zhengzhou Central Hospital Affiliated of Zhengzhou University, Zhengzhou 450007, China. 3. Department of Gastrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China.
Abstract
Objective: To construct the competitive endogenous RNA (ceRNA) network related to gastric cancer and explore the molecular mechanism. Methods: The expression profiles of lncRNA, miRNA and mRNA in gastric cancer and paracancer tissues were analyzed by biochip technology, edgeR package in R software was used to filtrate differential expression genes (multiple change of >1.5 times, P<0.05) and volcano map was drawn. Based on the online miRNA-lncRNA prediction tool lncBase database and the miRNA Target gene prediction database (miRTarBase, target-scan, miRDB, starBase), the relationship between miRNA, lncRNA and mRNA was predicted. Cytoscape software was used to construct lncRNA-miRNA-mRNA ceRNA network and key genes (hub genes) were identified based on cytohubba calculation of degree score of each node. Then Hub genes related to the prognosis of gastric cancer were verified in the TCGA database. The GO and KEGG enrichment analysis of differentially expressed mRNA was performed using the online biological information annotation database DAVID, P<0.05 and false discovery rate (FDR)<0.05 were used as cut-off criteria. R software was used to download the RNA sequencing data and mirna-seq data of gastric cancer and adjacent tissues in TCGA database, edgeR package was used to screen out differentially expressed mRNA, miRNA and lncRNA, and some differentially expressed genes in our data were verified. In OncoLnc database, STAD project of TCGA data was selected and hub gene was input. Patients were divided into two groups based on the median value for hub genes and Kaplan-meier analysis was performed. Results: The differentially expressed 766 mRNA, 110 lncRNA and 10 miRNA were screened out, among them 90 mRNA, 4 lncRNA and 6 miRNA were used to construct the ceRNA network, and 2 of the 20 hub genes were related to the prognosis of patients. MLK7-AS1, SPP1, SULF1, hsa-miR-1307-3p were upregulated in gastric cancer tissues from our biochip, while MT2A, MT1X were downregulated, which were consistent with the results of TCGA gastric cancer database. The differentially expressed mRNAs were significantly enriched in the biological process (BP) and the mineral absorption pathway. CHST1 was negatively correlated while miR-183-5p was positively corelated with the survival of patients. Conclusion: The establishment of ceRNA network for gastric cancer is conducive to further understanding of the molecular biological mechanism. CHST1 and miR-183-5p can be used as prognostic factors of gastric cancer.
Objective: To construct the competitive endogenous RNA (ceRNA) network related to gastric cancer and explore the molecular mechanism. Methods: The expression profiles of lncRNA, miRNA and mRNA in gastric cancer and paracancer tissues were analyzed by biochip technology, edgeR package in R software was used to filtrate differential expression genes (multiple change of >1.5 times, P<0.05) and volcano map was drawn. Based on the online miRNA-lncRNA prediction tool lncBase database and the miRNA Target gene prediction database (miRTarBase, target-scan, miRDB, starBase), the relationship between miRNA, lncRNA and mRNA was predicted. Cytoscape software was used to construct lncRNA-miRNA-mRNA ceRNA network and key genes (hub genes) were identified based on cytohubba calculation of degree score of each node. Then Hub genes related to the prognosis of gastric cancer were verified in the TCGA database. The GO and KEGG enrichment analysis of differentially expressed mRNA was performed using the online biological information annotation database DAVID, P<0.05 and false discovery rate (FDR)<0.05 were used as cut-off criteria. R software was used to download the RNA sequencing data and mirna-seq data of gastric cancer and adjacent tissues in TCGA database, edgeR package was used to screen out differentially expressed mRNA, miRNA and lncRNA, and some differentially expressed genes in our data were verified. In OncoLnc database, STAD project of TCGA data was selected and hub gene was input. Patients were divided into two groups based on the median value for hub genes and Kaplan-meier analysis was performed. Results: The differentially expressed 766 mRNA, 110 lncRNA and 10 miRNA were screened out, among them 90 mRNA, 4 lncRNA and 6 miRNA were used to construct the ceRNA network, and 2 of the 20 hub genes were related to the prognosis of patients. MLK7-AS1, SPP1, SULF1, hsa-miR-1307-3p were upregulated in gastric cancer tissues from our biochip, while MT2A, MT1X were downregulated, which were consistent with the results of TCGA gastric cancer database. The differentially expressed mRNAs were significantly enriched in the biological process (BP) and the mineral absorption pathway. CHST1 was negatively correlated while miR-183-5p was positively corelated with the survival of patients. Conclusion: The establishment of ceRNA network for gastric cancer is conducive to further understanding of the molecular biological mechanism. CHST1 and miR-183-5p can be used as prognostic factors of gastric cancer.