Fan Zhi-Yuan, Liu Wentao, Yan Chao, Zhu Zheng-Lun, Xu Wei, Li Jian-Fang, Su Liping, Li Chen, Zhu Zheng-Gang, Liu Bingya, Yan Min
Shanghai Key Laboratory of Gastric Neoplasms, Department of Surgery, Shanghai Institute of Digestive Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Tumour Biol. 2016 Oct;37(10):13265-13277. doi: 10.1007/s13277-016-5185-9. Epub 2016 Jul 26.
Gastric cancer (GC) is one of the most aggressive malignancies and has a poor prognosis. Identifying novel diagnostic and prognostic markers is of great importance for the management and treatment of GC. Long non-coding RNAs (lncRNAs), which are involved in multiple processes during the development and progression of cancer, may act as potential biomarkers of GC. Here, by performing data mining using four microarray data sets of GC downloaded from the Gene Expression Omnibus (GEO) database with different classifiers and risk score analyses, we identified a five-lncRNA signature (AK001094, AK024171, AK093735, BC003519 and NR_003573) displaying both diagnostic and prognostic values for GC. The results of the Kaplan-Meier survival analysis and log-rank test showed that the risk score based on this five-lncRNA signature was closely associated with overall survival time (p = 0.0001). Further analysis revealed that the risk score is an independent predictor of prognosis. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis of 30 pairs of GC tissue samples confirmed that the five lncRNAs were dysregulated in GC, and receiver operating characteristic (ROC) curves showed the high diagnostic ability of combining the five lncRNAs, with an area under the curve (AUC) of 0.95 ± 0.025. The five lncRNAs involved in several cancer-related pathways were identified using gene set enrichment analysis (GSEA). These findings indicate that the five-lncRNA signature may have a good clinical applicability for determining the diagnosis and predicting the prognosis of GC.
胃癌(GC)是最具侵袭性的恶性肿瘤之一,预后较差。识别新的诊断和预后标志物对于GC的管理和治疗至关重要。长链非编码RNA(lncRNA)参与癌症发生发展的多个过程,可能作为GC的潜在生物标志物。在此,我们通过使用从基因表达综合数据库(GEO)下载的四个GC微阵列数据集,采用不同分类器和风险评分分析进行数据挖掘,鉴定出一个五lncRNA特征(AK001094、AK024171、AK093735、BC003519和NR_003573),其对GC具有诊断和预后价值。Kaplan-Meier生存分析和对数秩检验结果表明,基于该五lncRNA特征的风险评分与总生存时间密切相关(p = 0.0001)。进一步分析显示,该风险评分是预后的独立预测因子。对30对GC组织样本进行的定量逆转录聚合酶链反应(qRT-PCR)分析证实,这五个lncRNA在GC中表达失调,受试者工作特征(ROC)曲线显示,联合这五个lncRNA具有较高的诊断能力,曲线下面积(AUC)为0.95±0.025。使用基因集富集分析(GSEA)鉴定出这五个lncRNA参与了多个癌症相关通路。这些发现表明,五lncRNA特征在确定GC诊断和预测预后方面可能具有良好的临床适用性。