Yu Yalan, Zuo Jiangcheng, Tan Qian, Zar Thin Khaing, Li Ping, Zhu Man, Yu Mingxia, Fu Zhenming, Liang Chunzi, Tu Jiancheng
Department of Laboratory Medicine, Clinical Laboratory Medicine and Center for Gene Diagnosis, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.
Department of Laboratory Medicine, Maternal and Child Health Hospital of Yiling, Yichang, Hubei, China.
Cancer Biomark. 2017;18(3):319-327. doi: 10.3233/CBM-160254.
MicroRNAs (miRNAs) are small, non-coding RNAs that play important roles in the carcinogenesis and progression of cancers. Aberrant expression of miRNAs in tissue and plasma has been found in various solid tumors. Our research aims to determine whether the abnormal plasma miRNA expression patterns can be used as a predictive marker for the diagnosis and prognosis of small cell lung cancer (SCLC). Fifty SCLC patients and 30 healthy controls annotated with clinical characteristics and specific questionnaire survey for smoking history were available. Quantification of several miRNAs (miR-20a-5p, miR-92a-2-5p and miR-17-5p) was performed using quantitative real-time polymerase chain reaction (qRT-PCR), and results were analyzed using SPSS statistics 17.0. Plasma miR-92a-2 level was significantly higher in the SCLC patients group compared with healthy control (P< 0.0001), the receiver operating characteristic (ROC) curve analysis showed that the specificity and sensitivity were at 100% and 56% for diagnosis of SCLC, area under the ROC curve (AUC) was 0.761. No other statistically significant differences were found in the expression level of plasma miR-92a-2 among survival analysis in SCLC. Detection of miR-92a-2 levels in plasma could be a potential and noninvasive method for the diagnosis of SCLC.
微小RNA(miRNA)是一类小的非编码RNA,在癌症的发生和发展过程中发挥着重要作用。在各种实体瘤中均发现组织和血浆中miRNA表达异常。我们的研究旨在确定血浆中异常的miRNA表达模式是否可作为小细胞肺癌(SCLC)诊断和预后的预测标志物。本研究纳入了50例SCLC患者和30名健康对照者,并记录了他们的临床特征以及通过特定问卷调查获取的吸烟史。采用定量实时聚合酶链反应(qRT-PCR)对几种miRNA(miR-20a-5p、miR-92a-2-5p和miR-17-5p)进行定量分析,并使用SPSS 17.0统计学软件对结果进行分析。SCLC患者组血浆miR-92a-2水平显著高于健康对照组(P<0.0001),受试者工作特征(ROC)曲线分析显示,其对SCLC诊断的特异性和敏感性分别为100%和56%,ROC曲线下面积(AUC)为0.761。在SCLC生存分析中,血浆miR-92a-2的表达水平未发现其他具有统计学意义的差异。检测血浆中miR-92a-2水平可能是一种潜在的、非侵入性的SCLC诊断方法。