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Published on: September 15, 2023
Identification of a potential competing endogenous RNA (ceRNA) network in gastric adenocarcinoma
Chen Wu1, Xinfang Hou1, Shuai Li1
1Department of Internal Medicine, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China.
Background:
Recently, a growing body of evidence has revealed the role of competing endogenous RNA (ceRNA) networks in various human cancers. However, there is still a lack of research on the systemic ceRNA network related to gastric adenocarcinoma.
Methods:
The intersection of differentially expressed genes (DEGs) was obtained by mining the GSE54129, GSE13861, and GSE118916 datasets from the Gene Expression Omnibus (GEO) website. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for the enrichment analysis. A protein-protein interaction (PPI) network was established with the STRING online database, and hub genes were identified by Cytoscape software. The prediction of key microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) was conducted by miRNet. The prognostic analysis, expression difference, and correlation analysis of messenger RNAs (mRNAs), lncRNAs, and miRNAs were carried out using the Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan-Meier plotter, and Encyclopedia of RNA Interactomes (ENCORI).
Results:
We identified180 significant DEGs. Extracellular matrix (ECM) receptor interaction, focal adhesion, ECM tissue, and collagen catabolic processes were the most significant pathways in the functional enrichment analysis. Nineteen upregulated hub genes and one downregulated hub gene were found to be significantly associated with the prognosis of gastric adenocarcinoma. Of the 18 miRNAs targeting 12 key genes, only six were associated with a promising prognosis in gastric adenocarcinoma. By comprehensive differential expression and survival analysis, 40 key lncRNAs were identified. Finally, we constructed a network of 24 ceRNAs associated with gastric adenocarcinoma.
Conclusions:
Potential mRNA-miRNA-lncRNA subnets were constructed, each RNA of which can be used as a prognostic biomarker for gastric adenocarcinoma.
Insights
This study identifies key RNAs in gastric adenocarcinoma, constructing a competing endogenous RNA (ceRNA) network. These RNAs show potential as prognostic biomarkers for gastric cancer, aiding future diagnostics and treatments.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Competing endogenous RNA (ceRNA) networks are increasingly recognized for their role in human cancers.
- Research on systemic ceRNA networks in gastric adenocarcinoma remains limited.
Purpose of the Study:
- To investigate the ceRNA network in gastric adenocarcinoma.
- To identify potential prognostic biomarkers for gastric cancer.
Main Methods:
- Utilized Gene Expression Omnibus (GEO) datasets (GSE54129, GSE13861, GSE118916) to identify differentially expressed genes (DEGs).
- Performed enrichment analysis using DAVID, constructed a protein-protein interaction (PPI) network with STRING, and identified hub genes via Cytoscape.
- Predicted microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) using miRNet and analyzed their prognostic value with GEPIA, Kaplan-Meier plotter, and ENCORI.
Main Results:
- Identified 180 significant DEGs and key pathways including ECM receptor interaction and focal adhesion.
- Found 20 hub genes significantly associated with gastric adenocarcinoma prognosis.
- Identified 40 key lncRNAs and constructed a 24 ceRNA network, with six miRNAs showing promising prognostic value.
Conclusions:
- Constructed potential messenger RNA (mRNA)-miRNA-lncRNA subnets for gastric adenocarcinoma.
- Each RNA within these subnets can serve as a prognostic biomarker for gastric adenocarcinoma.
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