Conclusion
Prognostic indicators of EAC may be useful in future EAC diagnosis and treatment.
Methods
The EAC dataset from The Cancer Genome Atlas was screened for differentially expressed microRNAs (miRNAs) and mRNAs associated with EAC. Weighted gene coexpression network analysis was performed to cluster miRNAs or mRNA with similar expression patterns to identify the miRNAs or mRNA that are highly associated with EAC. Prognostic miRNAs for overall survival (OS) were identified using Cox proportional-hazards regression analysis and least absolute shrinkage and selection operator based on survival duration and status. Two types of miRNAs were selected to develop a prognostic signature model for EAC using multiple Cox regression analysis. Furthermore, the signature was validated using internal validation sets 1 and 2. The receiver operating characteristic curve and concordance index were used to evaluate the accuracy of the signature and validation sets. The expression of miR-421, miR-550a-3p, and miR-550a-5p was assessed using quantitative polymerase chain reaction (qPCR). The proliferation, invasion, and migration of EAC cells were assessed using CCK8 and transwell assays. The OS of target mRNAs was assessed using Kaplan-Meier analysis. Functional enrichment analysis of the target mRNAs was performed using Metascape.
Objective
To identify the prognostic indicators of esophageal adenocarcinoma (EAC) for future EAC diagnosis and treatment.
Results
The prognostic signature and validation sets comprising mir-421 and mir-550a-1 had favorable predictive power in OS. Compared with the patients with EAC in the high-expression group, those assigned to the low-expression group displayed increased OS according to survival analysis. Differential and qPCR analysis showed that miR-421, miR-550a-3p, and miR-550a-5p were highly expressed in the EAC tissues and cell lines. Moreover, the downregulation of miR-421 and miR-550a-3p with inhibitor markedly suppressed the proliferation, invasion, and migration in OE33 cells compared with the negative control. A total of 20 target mRNAs of three miRNAs were predicted, among which seven target mRNAs-ASAP3, BCL2L2, LMF1, PPM1L, PTPN21, SLC18A2, and NR3C2-had prognostic value; PRKACB, PDCD4, RPS6KA5, and BCL2L2 were enriched in the miRNA cancer pathway.