Oncotarget

Research Papers:

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

Xiumei Jiang, Wenfei Wang, Yongmei Yang, Lutao Du, Xiaoyun Yang, Lili Wang, Guixi Zheng, Weili Duan, Rui Wang, Xin Zhang, Lishui Wang, Xiaoyang Chen and Chuanxin Wang _

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Oncotarget. 2017; 8:65132-65142. https://doi.org/10.18632/oncotarget.17789

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Abstract

Xiumei Jiang1,*, Wenfei Wang2,*, Yongmei Yang3, Lutao Du3, Xiaoyun Yang3, Lili Wang3, Guixi Zheng3, Weili Duan1, Rui Wang1, Xin Zhang3, Lishui Wang3, Xiaoyang Chen2 and Chuanxin Wang1

1Department of Clinical Laboratory, The Second Hospital of Shandong University, Jinan, 250033, Shandong Province, China

2Humanistic Medicine Research Center, Shandong University, Jinan, 250012, Shandong Province, China

3Department of Clinical Laboratory, Qilu Hospital, Shandong University, Jinan, 250012, Shandong Province, China

*These authors contributed equally to this work

Correspondence to:

Chuanxin Wang, email: [email protected]

Keywords: microRNA, lymph node metastasis, gastric cancer, prediction, prognosis

Received: January 10, 2017     Accepted: April 05, 2017     Published: May 10, 2017

ABSTRACT

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 < 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.


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