Conclusion
Our results illustrate that the panel of EV circRNAs in serum are aberrantly expressed and may act as the suitable biomarkers for gastric cancer.
Methods
High-throughput RNA sequencing (RNA-seq) was used to assess circRNA expression profiles between 4 patients with GC and 4 healthy controls. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were employed to determine the biological functions of differentially expressed (DE) circRNAs. A circRNA-miRNA-mRNA network was constructed using bioinformatics tools. Reverse transcription-quantitative polymerase chain reaction (RT-q)PCR was used to validate the dysregulated circRNAs. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic value of circRNAs for GC.
Objective
At present, there are still no effective diagnosis
Results
A total of 4692 circRNAs were detected in the serum EVs of healthy controls and patients with GC, most of which were novel (98%) and intergenic (52%). 7 circRNAs were upregulated and 4 circRNAs were downregulated (|log2Fold Change| > 2, P < 0.05). GO and KEGG pathway enrichment analyses revealed that DE circRNAs were primarily involved in glutathione metabolism, protein folding, and drug metabolism-cytochrome P450. Of these, 3 circRNAs (Chr10q11, Chr1p11, and Chr7q11) were identified to be significantly overexpressed in patients with GC compared with healthy controls using RT-qPCR. The combination of 3 EV circRNAs and carcinoembryonic antigen (CEA) produced an area under the curve (AUC) of 0.866 (95%CI: 0.803-0.915) with a sensitivity and specificity of 80.4% and 81.8%, respectively. Additionally, the expression levels of 3 EV circRNAs were significantly correlated with tumor size, lymph node metastasis, and TNM stage. The circRNA-miRNA-mRNA network showed that the 3 identified circRNAs were predicted to interact with 13 miRNAs and 91 mRNAs.