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We previously analyzed the microRNA (miRNA) expression pattern in gastriccancer with and without recurrence and obtained 17 differentially expressed miRNAswith potential to predict recurrence risk for GC patients. In the present study,we aimed to investigate recurrence-related genes which may be regulated by thedifferentially expressed miRNAs identified in our prior research. Three differentmiRNA target gene databases (miRanda, TargetScan and PicTar) were used for searchingthe potential genes regulated by miRNAs. A combination was performed between miRNAtarget genes and recurrence-related gene expression profiling. Three bioinformaticsalgorithms (PAM, SVM and RF) were used to feature recurrence-related gene selection.In addition, we validated the expression levels of the genes in GC patients usingreal-time PCR. A total of 3,263 genes were identified as potential targets of17 miRNAs. We identified 2,736 differential expressed genes using the SAM methodbased on 22K oligo microarray data which included 7 recurrence and 4 without recurrenceGC samples. Combining the target genes regulated by miRNAs and the differentiallyexpressed genes between recurrence and non-recurrence groups, we identified 228differential genes for further study. Finally, we identified HNRPA0 and PRDM4as risk biomarkers of GC patients, which were regulated by hsa-miR‑194 and hsa-miR-373,respectively. Our data indicated that HNRPA0 and PRDM4 may be involved in therecurrence process of GC and have potential to act as new prognostic biomarkersin predicting recurrence risk for gastric cancer patients.

Identification of recurrence-related genes by integrating microRNA and gene expression profiling of gastric cancer