Jiang Xiumei, Wang Wenfei, Yang Yongmei, Du Lutao, Yang Xiaoyun, Wang Lili, Zheng Guixi, Duan Weili, Wang Rui, Zhang Xin, Wang Lishui, Chen Xiaoyang, Wang Chuanxin
Department of Clinical Laboratory, The Second Hospital of Shandong University, Jinan, 250033, Shandong Province, China.
Humanistic Medicine Research Center, Shandong University, Jinan, 250012, Shandong Province, China.
Oncotarget. 2017 May 10;8(39):65132-65142. doi: 10.18632/oncotarget.17789. eCollection 2017 Sep 12.
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 ( 279) and a validation cohort ( 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) ( < 0.05). In Cox regression analysis, miR-451a was independently associated with OS of LNM ( = 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.
循环微小RNA(miRNA)正逐渐成为预测癌症淋巴结转移(LNM)的新型非侵入性生物标志物。本研究旨在鉴定用于预测和评估胃癌(GC)患者LNM的血清miRNA特征。对10例伴有LNM的GC患者、10例无LNM的患者和10例健康对照者的血清miRNA进行了MiSeq测序初步筛选。采用逆转录定量实时PCR,利用训练队列(279例)和验证队列(180例)来确认候选miRNA的浓度。我们通过多变量逻辑回归模型确定了一个包含4种miRNA的组合(miR-501-3p、miR-143-3p、miR-451a、miR-146a),该组合对LNM具有较高的预测准确性,在训练集中受试者操作特征曲线(AUC)下面积为0.891(95%CI,0.840至0.930)。对该组合的前瞻性评估显示,在验证集中AUC为0.822(95%CI,0.758至0.875,特异性 = 87.78%,敏感性 = 63.33%)。此外,Kaplan-Meier分析表明,miR-451a和miR-146a水平较低的LNM患者总生存期(OS)较差(P<0.05)。在Cox回归分析中,miR-451a与LNM患者的OS独立相关(P = 0.028)。我们的结果表明,使用血清miRNA在估计GC患者发生LNM的概率以及为LNM提供预后信息方面似乎很有前景。