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Circulating microRNAs (miRNAs) are emerging as novel noninvasive biomarkers for prediction of lymph node metastasis (LNM) in cancer. The aim of this study was to identify serum miRNA signatures for prediction and prognosis of LNM in gastric cancer (GC). MiSeq sequencing was performed for an initial screening of serum miRNAs in 10 GC patients with LNM, 10 patients without LNM and 10 healthy controls. Reverse transcription quantitative real-time PCR was applied to confirm concentration of candidate miRNAs using a training cohort ( n = 279) and a validation cohort ( n = 180). We identified a four-miRNA panel (miR-501-3p, miR-143-3p, miR-451a, miR-146a) by multivariate logistic regression model that provided high predictive accuracy for LNM with an area under the receiver operating characteristic curve (AUC) of 0.891 (95% CI, 0.840 to 0.930) in training set. Prospective evaluation of this panel revealed an AUC of 0.822 (95% CI, 0.758 to 0.875, specificity = 87.78%, sensitivity = 63.33%) in validation set. Moreover, Kaplan-Meier analysis showed that LNM patients with low miR-451a and miR-146a levels had worse overall survival (OS) ( p &lt; 0.05). In Cox regression analysis, miR-451a was independently associated with OS of LNM ( p = 0.028). Our results suggested that use of serum miRNAs seems promising in estimating the probability GC patients harbor LNM and providing prognostic information for LNM.

oncotarget

Identification of circulating microRNA signatures as potential noninvasive biomarkers for prediction and prognosis of lymph node metastasis in gastric cancer