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整合的癌症基因组图谱(TCGA)分析表明,长链非编码RNA CTB-193M12.5是肺腺癌的一个预后因素。

Integrated TCGA analysis implicates lncRNA CTB-193M12.5 as a prognostic factor in lung adenocarcinoma.

作者信息

Wang Xuehai, Li Gang, Luo Qingsong, Xie Jiayong, Gan Chongzhi

机构信息

Department of Thoracic Surgery, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, 32 West Second Section First Ring Road, Chengdu, 610072 Sichuan People's Republic of China.

出版信息

Cancer Cell Int. 2018 Feb 22;18:27. doi: 10.1186/s12935-018-0513-3. eCollection 2018.

Abstract

BACKGROUND

Lung cancer is a malignant tumor with the highest incidence and mortality around the world. Recent advances in RNA sequencing technology have enabled insights into long non-coding RNAs (lncRNAs), a previously largely overlooked species in dissecting lung cancer pathology.

METHODS

In this study, we used a comprehensive bioinformatics analysis strategy to identify lncRNAs closely associated with lung adenocarcinoma, using the RNA sequencing datasets collected from more than 500 lung adenocarcinoma patients and deposited at The Cancer Genome Atlas (TCGA) database.

RESULTS

Differential expression analysis highlighted lncRNAs CTD-2510F5.4 and CTB-193M12.5, both of which were significantly upregulated in cancerous specimens. Moreover, network analyses showed highly correlated expression levels of both lncRNAs with those of differentially expressed protein-coding genes, and suggested central regulatory roles of both lncRNAs in the gene co-expression network. Importantly, expression of CTB-193M12.5 showed strong negative correlation with patient survival.

CONCLUSIONS

Our study mined existing TCGA datasets for novel factors associated with lung adenocarcinoma, and identified a largely unknown lncRNA as a potential prognostic factor. Further investigation is warranted to characterize the roles and significance of CTB-193M12.5 in lung adenocarcinoma biology.

摘要

背景

肺癌是全球发病率和死亡率最高的恶性肿瘤。RNA测序技术的最新进展使人们能够深入了解长链非编码RNA(lncRNA),这是一种在剖析肺癌病理学过程中此前基本被忽视的物种。

方法

在本研究中,我们使用了一种全面的生物信息学分析策略,利用从500多名肺癌腺癌患者收集并存储在癌症基因组图谱(TCGA)数据库中的RNA测序数据集,来识别与肺腺癌密切相关的lncRNA。

结果

差异表达分析突出了lncRNA CTD-2510F5.4和CTB-193M12.5,这两种lncRNA在癌组织标本中均显著上调。此外,网络分析显示这两种lncRNA的表达水平与差异表达的蛋白质编码基因高度相关,并表明这两种lncRNA在基因共表达网络中起核心调节作用。重要的是,CTB-193M12.5的表达与患者生存率呈强烈负相关。

结论

我们的研究挖掘了现有的TCGA数据集以寻找与肺腺癌相关的新因素,并确定了一种基本未知的lncRNA作为潜在的预后因素。有必要进一步研究以阐明CTB-193M12.5在肺腺癌生物学中的作用和意义。

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