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A comprehensive study of construction and analysis of competitive endogenous RNA networks in lung adenocarcinoma.
Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics ( IF 2.5 ) Pub Date : 2020-05-11 , DOI: 10.1016/j.bbapap.2020.140444
Chang Gu 1 , Xin Shi 2 , Zhenyu Huang 3 , Jiafei Chen 1 , Jun Yang 4 , Jianxin Shi 4 , Xufeng Pan 4
Affiliation  

BACKGROUND Long noncoding RNAs (lncRNAs) have gain increasing attention in lung adenocarcinoma. In this study, we aimed at constructing and analyzing the lncRNAs and the related proteins based competitive endogenous RNA (ceRNA) network. METHODS RNA expression data of lung adenocarcinoma were extracted from the TCGA database. Differentially expressed (DE) lncRNAs, messenger RNAs (mRNAs) and microRNAs (miRNAs) were identified and then a DElncRNA-DEmiRNA-DEmRNA ceRNA network was constructed for lung adenocarcinoma. We also analyzed the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of the DEgenes. Kaplan-Meier survival curves were also been further utilized for exploring the prognostic factors. RESULTS After compared and calculated lncRNA, mRNA and miRNA expression profiles between lung adenocarcinoma and normal samples, 1709 differential expressed lncRNAs, 2554 differential expressed mRNAs and 116 differential expressed miRNAs were finally identified. Afterwards, a lncRNA mediated ceRNA network was constructed, according to the interactions among 544 pairs of DElncRNA-DEmiRNA relationships and 47 pairs of DEmiRNA-DEmRNA relationships. As for the survival analyses, we found 10 DElncRNAs, 25 DEmRNAs and 7 miRNAs have statistically prognostic significance for overall survival, respectively. CONCLUSIONS This study provides meaningful information for deeper understanding the underlying molecular mechanism of lung adenocarcinoma and for evaluating prognosis, which could monitor recurrence, guide clinical treatment drugs and subsequent related researches.

中文翻译:

肺腺癌竞争性内源性RNA网络的构建和分析的全面研究。

背景技术长非编码RNA(lncRNA)在肺腺癌中越来越受到关注。在这项研究中,我们旨在构建和分析基于竞争内源性RNA(ceRNA)网络的lncRNAs和相关蛋白。方法从TCGA数据库中提取肺腺癌的RNA表达数据。鉴定差异表达(DE)lncRNA,信使RNA(mRNA)和微小RNA(miRNA),然后构建用于肺腺癌的DElncRNA-DEmiRNA-DEmRNA ceRNA网络。我们还分析了DEgenes的基因本体论(GO)和《京都基因与基因组百科全书》(KEGG)途径富集。Kaplan-Meier生存曲线也被进一步用于探讨预后因素。结果经过比较和计算lncRNA,最终鉴定出肺腺癌与正常样品之间的mRNA和miRNA表达谱,1709个差异表达的lncRNA,2554个差异表达的mRNA和116个差异表达的miRNA。然后,根据544对DElncRNA-DEmiRNA关系和47对DEmiRNA-DEmRNA关系之间的相互作用,构建了一个lncRNA介导的ceRNA网络。至于生存分析,我们发现10个DElncRNA,25个DEmRNA和7个miRNA分别对总体生存具有统计学意义。结论这项研究为深入了解肺腺癌的潜在分子机制和评估预后提供了有意义的信息,这些信息可以监测复发,指导临床治疗药物和后续相关研究。最终鉴定出1709个差异表达的lncRNA,2554个差异表达的mRNA和116个差异表达的miRNA。然后,根据544对DElncRNA-DEmiRNA关系和47对DEmiRNA-DEmRNA关系之间的相互作用,构建了一个lncRNA介导的ceRNA网络。至于生存分析,我们发现10个DElncRNA,25个DEmRNA和7个miRNA分别对总体生存具有统计学意义。结论这项研究为深入了解肺腺癌的潜在分子机制和评估预后提供了有意义的信息,这些信息可以监测复发,指导临床治疗药物和后续相关研究。最终鉴定出1709个差异表达的lncRNA,2554个差异表达的mRNA和116个差异表达的miRNA。然后,根据544对DElncRNA-DEmiRNA关系和47对DEmiRNA-DEmRNA关系之间的相互作用,构建了一个lncRNA介导的ceRNA网络。至于生存分析,我们发现10个DElncRNA,25个DEmRNA和7个miRNA分别对总体生存具有统计学意义。结论这项研究为深入了解肺腺癌的潜在分子机制和评估预后提供了有意义的信息,这些信息可以监测复发,指导临床治疗药物和后续相关研究。然后,根据544对DElncRNA-DEmiRNA关系和47对DEmiRNA-DEmRNA关系之间的相互作用,构建了一个lncRNA介导的ceRNA网络。至于生存分析,我们发现10个DElncRNA,25个DEmRNA和7个miRNA分别对总体生存具有统计学意义。结论这项研究为深入了解肺腺癌的潜在分子机制和评估预后提供了有意义的信息,这些信息可以监测复发,指导临床治疗药物和后续相关研究。然后,根据544对DElncRNA-DEmiRNA关系和47对DEmiRNA-DEmRNA关系之间的相互作用,构建了一个lncRNA介导的ceRNA网络。至于生存分析,我们发现10个DElncRNA,25个DEmRNA和7个miRNA分别对总体生存具有统计学意义。结论这项研究为深入了解肺腺癌的潜在分子机制和评估预后提供了有意义的信息,这些信息可以监测复发,指导临床治疗药物和后续相关研究。25个DEmRNA和7个miRNA分别对总体生存具有统计学意义。结论这项研究为深入了解肺腺癌的潜在分子机制和评估预后提供了有意义的信息,这些信息可以监测复发,指导临床治疗药物和后续相关研究。25个DEmRNA和7个miRNA分别对总体生存具有统计学意义。结论这项研究为深入了解肺腺癌的潜在分子机制和评估预后提供了有意义的信息,这些信息可以监测复发,指导临床治疗药物和后续相关研究。
更新日期:2020-05-11
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