RNA-Sequencing and Bioinformatics Analysis of Exosomal Long Noncoding RNAs Revealed a Novel ceRNA Network in Stable COPD

外泌体长链非编码 RNA 的 RNA 测序和生物信息学分析揭示了稳定期 COPD 中的新型 ceRNA 网络

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作者:Shan Lin, Caihong Liu, Jingting Sun, Yinghui Guan

Conclusion

Our study provided a set of lncRNAs and mRNAs that may be involved in the pathogenesis of COPD, thereby highlighting the need for further research on both diagnostic biomarkers and molecular mechanisms.

Methods

High-throughput sequencing was conducted to detect the alterations in the expression of exosomal lncRNAs and mRNAs. Gene ontology (GO) functional analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to determine the significant functions and pathways associated with differentially expressed (DE) lncRNAs. The mRNA expression profile dataset, GSE76925, and microRNA expression profile dataset, GSE70080, were obtained from the GEO database. Venn diagrams were used to find common DE mRNAs between my mRNAs dataset and GSE76925. These common DEGs were subjected to PPI analyses to identify Hub genes. Subsequently, Venn diagrams were used to identify common genes between the target genes of DE-miRNAs and Hub genes as well as DE-miRNAs and my lncRNAs dataset. Finally, a lncRNA-miRNA-mRNA co-expression network was constructed by prediction using proprietary software. The lncRNA and mRNA expressions were then validated by quantitative reverse-transcription polymerase chain reaction (qRT-PCR).

Purpose

Exosomes are able to exchange their bioactive RNA cargo to recipient cells. In COPD, exosomes can be controlled and engineered for its use as targeted diagnostic and therapeutic tool. Our study explored novel lncRNAs and mRNAs in plasma exosomes that could be involved in the pathogenesis of COPD.

Results

We identified 1578 differentially regulated lncRNAs and 3071 differentially regulated mRNAs. GO and KEGG pathway analyses suggested that the DE lncRNAs are involved in the pathogenesis of COPD. A lncRNA-miRNA-mRNA meshwork was established to predict the potential interactions among these RNAs. RP3-329A5.8 and MRPS11 expression was then subjected to qRT-PCR for validation. Correlations between MRPS11 and clinic-pathological features were explored.

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