Background: Recurrence is a major factor leading to treatment failure and death in gastric cancer (GC) patients following surgical resection. Importantly, the prediction of recurrence is critical in improving clinical outcomes. We isolated a group of microRNAs (miRNAs) and evaluated their usefulness as prognostic markers for the recurrence of GC.
Patients and methods: A total of 65 GC patients were selected for systematic analysis, 29 patients with recurrence and 36 patients without recurrence. Firstly, miRNAs microarray and bioinformatics methods were used to characterize classifiers from primary tumor samples (n = 8). Following, we validated these predictors both in frozen fresh and paraffin-embedded tissue samples (n = 57) using quantitative PCR.
Results: We have identified 17 differential miRNAs including 10 up-regulated and 7 down-regulated miRNAs in recurrence group. Using k-top scoring pairs (k-TSP) method, we further ascertained hsa-miR-375 and hsa-miR-142-5p as a classifier to recognize recurrence and nonrecurrence cases both in the training and test samples. Moreover, we validated this classifier in 34 frozen fresh tissues and 38 paraffin-embedded tissues with consistent sensitivity and specificity with training set; among them, 15 cases were matched. A high frequency recurrence and poor survival were observed in GC cases with high level of hsa-miR-375 and low level of hsa-miR-142-5p (P < 0.001). In addition, we evaluated that hsa-miR-375 and hsa-miR-142-5p were involved in regulating target genes in several oncogenic signal pathways, such as TP53, MAPK, Wnt and vascular endothelial growth factor.
Conclusion: Our results indicate that the combination of hsa-miR-375 and hsa-miR-142-5p as a predictor of disease progression has the potential to predict recurrence risk for GC patients.