Genome-wide small nucleolar RNA expression analysis of lung cancer by next-generation deep sequencing
Genome-wide small nucleolar RNA expression analysis of lung cancer by next-generation deep sequencing
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DOI：
10.1002/ijc.29169
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发表时间：
2015-03-15
影响因子：
6.4
通讯作者：
Jiang, Feng
中科院分区：
文献类型：
--
作者：
Gao, Lu;Ma, Jie;Jiang, Feng
新的证据表明，小核仁rna （small nucleolar RNAs, snoRNAs）是一类小的非编码rna，可能在肿瘤发生中发挥重要作用。非小细胞肺癌（NSCLC）是男性和女性的头号癌症杀手。系统地表征NSCLC中的snorna将为其早期检测和预后开发生物标志物。我们使用下一代深度测序全面表征12个NSCLC组织中的snoRNA谱。我们采用定量逆转录聚合酶链反应（qRT-PCR）对40例手术I期NSCLC标本和126例不同分期的冷冻NSCLC组织进行验证。将126个NSCLC组织分为训练集和测试集。深度测序鉴定出458个snorna，其中29个在I期NSCLC组织中表达水平变化为正常组织的3.0倍。qRT-PCR分析显示，29个snorna中有16个与深度测序数据表现出一致的变化。16个snorna在受体-操作者特征曲线值下区分肺肿瘤和正常肺组织的面积为0.75 ~ 0.94（均为0.0001），敏感性为70.0 ~ 95.0%，特异性为70.0 ~ 95.0%。6个基因（snoRA47、snoRA68、snoRA78、snoRA21、snoRD28和snoRD66）的表达与NSCLC患者的总生存率相关。在77例NSCLC患者的训练集中建立了由3个基因（snoRA47、snoRA68和snoRA78）组成的预测模型，该模型能显著预测NSCLC患者的总生存期(p
Emerging evidence indicates that small nucleolar RNAs (snoRNAs), a class of small noncoding RNAs, may play important function in tumorigenesis. Nonsmall-cell lung cancer (NSCLC) is the number one cancer killer for men and women. Systematically characterizing snoRNAs in NSCLC will develop biomarkers for its early detection and prognostication. We used next-generation deep sequencing to comprehensively characterize snoRNA profiles in 12 NSCLC tissues. We used quantitative reverse transcription polymerase chain reaction (qRT-PCR) to verify the findings in 40 surgical Stage I NSCLC specimens and 126 frozen NSCLC tissues of different stages. The 126 NSCLC tissues were divided into a training set and a testing set. Deep sequencing identified 458 snoRNAs, of which, 29 had a 3.0-fold expression level change in Stage I NSCLC tissues versus normal tissues. qRT-PCR analysis showed that 16 of 29 snoRNAs exhibited consistent changes with deep sequencing data. The 16 snoRNAs exhibited 0.75-0.94 area under receiver-operator characteristic curve values in distinguishing lung tumor from normal lung tissues (all 0.0001) with 70.0-95.0% sensitivity and 70.0-95.0% specificity. Six genes (snoRA47, snoRA68, snoRA78, snoRA21, snoRD28 and snoRD66) were identified whose expressions were associated with overall survival of the NSCLC patients. A prediction model consisting of three genes (snoRA47, snoRA68 and snoRA78) was developed in the training set of 77 cases, which could significantly predict overall survival of the NSCLC patients (p