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突变衍生的长链非编码RNA特征预测肺腺癌的生存情况。

Mutation-Derived Long Noncoding RNA Signature Predicts Survival in Lung Adenocarcinoma.

作者信息

Yang Longjun, Guo Guangran, Yu Xiangyang, Wen Yingsheng, Lin Yongbin, Zhang Rusi, Zhao Dechang, Huang Zirui, Wang Gongming, Yan Yan, Zhang Xuewen, Chen Dongtai, Xing Wei, Wang Weidong, Zeng Weian, Zhang Lanjun

机构信息

State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.

Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China.

出版信息

Front Oncol. 2022 Mar 15;12:780631. doi: 10.3389/fonc.2022.780631. eCollection 2022.

Abstract

BACKGROUND

Genomic instability is one of the representative features of cancer evolution. Recent research has revealed that long noncoding RNAs (lncRNAs) play a critical role in maintaining genomic instability. Our work proposed a gene signature (GILncSig) based on genomic instability-derived lncRNAs to probe the possibility of lncRNA signatures as an index of genomic instability, providing a potential new approach to identify genomic instability-related cancer biomarkers.

METHODS

Lung adenocarcinoma (LUAD) gene expression data from an RNA-seq FPKM dataset, somatic mutation information and relevant clinical materials were downloaded from The Cancer Genome Atlas (TCGA). A prognostic model consisting of genomic instability-related lncRNAs was constructed, termed GILncSig, to calculate the risk score. We validated GILncSig using data from the Gene Expression Omnibus (GEO) database. In this study, we used R software for data analysis.

RESULTS

Through univariate and multivariate Cox regression analyses, five genomic instability-associated lncRNAs (, and ) were identified. We constructed a lncRNA signature (GILncSig) related to genomic instability. LUAD patients were classified into two risk groups by GILncSig. The results showed that the survival rate of LUAD patients in the low-risk group was higher than that of those in the high-risk group. Then, we verified GILncSig in the GEO database. GILncSig was associated with the genomic mutation rate of LUAD. We also used GILncSig to divide TP53 mutant-type patients and TP53 wild-type patients into two groups and performed prognostic analysis. The results suggested that compared with TP53 mutation status, GILncSig may have better prognostic significance.

CONCLUSIONS

By combining the lncRNA expression profiles associated with somatic mutations and the corresponding clinical characteristics of LUAD, a lncRNA signature (GILncSig) related to genomic instability was established.

摘要

背景

基因组不稳定是癌症进化的代表性特征之一。最近的研究表明,长链非编码RNA(lncRNAs)在维持基因组不稳定中起关键作用。我们的工作基于基因组不稳定衍生的lncRNAs提出了一种基因特征(GILncSig),以探究lncRNA特征作为基因组不稳定指标的可能性,为识别基因组不稳定相关癌症生物标志物提供了一种潜在的新方法。

方法

从癌症基因组图谱(TCGA)下载来自RNA-seq FPKM数据集的肺腺癌(LUAD)基因表达数据、体细胞突变信息及相关临床资料。构建了一个由基因组不稳定相关lncRNAs组成的预后模型,称为GILncSig,用于计算风险评分。我们使用基因表达综合数据库(GEO)的数据验证了GILncSig。在本研究中,我们使用R软件进行数据分析。

结果

通过单因素和多因素Cox回归分析,鉴定出5个与基因组不稳定相关的lncRNAs(、和)。我们构建了一个与基因组不稳定相关的lncRNA特征(GILncSig)。GILncSig将LUAD患者分为两个风险组。结果表明,低风险组LUAD患者的生存率高于高风险组。然后,我们在GEO数据库中验证了GILncSig。GILncSig与LUAD的基因组突变率相关。我们还使用GILncSig将TP53突变型患者和TP53野生型患者分为两组并进行预后分析。结果表明,与TP53突变状态相比,GILncSig可能具有更好的预后意义。

结论

通过结合与体细胞突变相关的lncRNA表达谱和LUAD的相应临床特征,建立了一个与基因组不稳定相关的lncRNA特征(GILncSig)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eda9/8965709/0a6ce29b2f02/fonc-12-780631-g001.jpg

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