Integrative microRNA and gene profiling data analysis reveals novel biomarkers and mechanisms for lung cancer.
Integrative microRNA and gene profiling data analysis reveals novel biomarkers and mechanisms for lung cancer.
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DOI：
10.18632/oncotarget.7264
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发表时间：
2016-02-23
期刊：
影响因子：
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通讯作者：
Deng Y
中科院分区：
文献类型：
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作者：
Hu L;Ai J;Long H;Liu W;Wang X;Zuo Y;Li Y;Wu Q;Deng Y
关于 microRNA (miRNA) 诊断非小细胞肺癌 (NSCLC) 准确性的研究仍存在争议。因此，我们利用微阵列数据集系统地鉴定与NSCLC相关的miRNA及其靶基因表达变化。我们从Gene Expression Omnibus中筛选出5个miRNA和6个基因微阵列数据集，其中包含NSCLC中的miRNA和基因表达。我们的分析结果表明，14 个 miRNA 在 NSCLC 中显着失调。其中 5 个上调（miR-9、miR-708、miR-296-3p、miR-892b、miR-140-5P），而 9 个下调（miR-584、miR-218、miR-30b、miR-522、miR486-5P、miR-34c-3p、miR-34b、miR-516b、 miR-592）。综合诊断敏感性（SE）和特异性（SP）分别为82.6%和89.9%。我们还发现 4 个目标基因（p < 0.05，倍数变化 > 2.0）与 14 个发现的 miRNA 显着相关，并且我们从一个训练集构建的分类器以更高的准确度预测验证集（SE = 0.987，SP = 0.824）。我们的结果表明，整合 miRNA 和靶基因对于识别有前景的生物标志物非常有价值，并为 NSCLC 的潜在机制提供了新的见解。此外，我们精心设计的验证研究肯定有必要研究与这 14 种 miRNA 相关的靶基因在 NSCLC 的预测和发展中的作用。
Studies on the accuracy of microRNAs (miRNAs) in diagnosing non-small cell lung cancer (NSCLC) have still controversial. Therefore, we conduct to systematically identify miRNAs related to NSCLC, and their target genes expression changes using microarray data sets. We screened out five miRNAs and six genes microarray data sets that contained miRNAs and genes expression in NSCLC from Gene Expression Omnibus. Our analysis results indicated that fourteen miRNAs were significantly dysregulated in NSCLC. Five of them were up-regulated (miR-9, miR-708, miR-296-3p, miR-892b, miR-140-5P) while nine were down-regulated (miR-584, miR-218, miR-30b, miR-522, miR486-5P, miR-34c-3p, miR-34b, miR-516b, miR-592). The integrating diagnosis sensitivity (SE) and specificity (SP) were 82.6% and 89.9%, respectively. We also found that 4 target genes (p < 0.05, fold change > 2.0) were significant correlation with the 14 discovered miRNAs, and the classifiers we built from one training set predicted the validation set with higher accuracy (SE = 0.987, SP = 0.824). Our results demonstrate that integrating miRNAs and target genes are valuable for identifying promising biomarkers, and provided a new insight on underlying mechanism of NSCLC. Further, our well-designed validation studies surely warrant the investigation of the role of target genes related to these 14 miRNAs in the prediction and development of NSCLC.