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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 COPD 中的新型 ceRNA 网络。

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

机构信息

Department of Respiratory Medicine, The First Hospital of Jilin University, Changchun, Jilin, People's Republic of China.

Department of Clinical Laboratory, The First Hospital of Jilin University, Changchun, Jilin, People's Republic of China.

出版信息

Int J Chron Obstruct Pulmon Dis. 2023 Sep 11;18:1995-2007. doi: 10.2147/COPD.S414901. eCollection 2023.

DOI:10.2147/COPD.S414901
PMID:37720876
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10503524/
Abstract

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.

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).

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.

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.

摘要

目的

外泌体能够交换其生物活性 RNA 货物到受体细胞。在 COPD 中,外泌体可以被控制和设计用于作为靶向诊断和治疗工具。我们的研究探索了血浆外泌体中可能参与 COPD 发病机制的新型长链非编码 RNA (lncRNA) 和信使 RNA (mRNA)。

方法

进行高通量测序以检测外泌体 lncRNA 和 mRNA 表达的变化。基因本体 (GO) 功能分析和京都基因与基因组百科全书 (KEGG) 途径分析用于确定与差异表达 (DE) lncRNA 相关的显著功能和途径。mRNA 表达谱数据集 GSE76925 和 microRNA 表达谱数据集 GSE70080 从 GEO 数据库中获得。使用 Venn 图寻找我 mRNA 数据集和 GSE76925 之间的共同 DE mRNA。这些共同的 DEGs 进行 PPI 分析以识别 Hub 基因。随后,使用 Venn 图来识别 DE-miRNA 和 Hub 基因以及 DE-miRNA 和我的 lncRNA 数据集之间的共同基因。最后,通过专有软件的预测构建 lncRNA-miRNA-mRNA 共表达网络。通过定量逆转录聚合酶链反应 (qRT-PCR) 验证 lncRNA 和 mRNA 的表达。

结果

我们鉴定了 1578 个差异调节的 lncRNA 和 3071 个差异调节的 mRNA。GO 和 KEGG 途径分析表明,DE lncRNA 参与 COPD 的发病机制。建立了 lncRNA-miRNA-mRNA 网格来预测这些 RNA 之间的潜在相互作用。然后进行 qRT-PCR 验证 RP3-329A5.8 和 MRPS11 的表达。探索了 MRPS11 与临床病理特征之间的相关性。

结论

我们的研究提供了一组可能参与 COPD 发病机制的 lncRNA 和 mRNA,从而强调了对诊断生物标志物和分子机制的进一步研究的必要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bba9/10503524/6a8be5db1f6c/COPD-18-1995-g0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bba9/10503524/a7ad489234d5/COPD-18-1995-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bba9/10503524/10f25d0a8674/COPD-18-1995-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bba9/10503524/828c5deecae0/COPD-18-1995-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bba9/10503524/b94de2ab7384/COPD-18-1995-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bba9/10503524/7fde117f716c/COPD-18-1995-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bba9/10503524/ca5862ac8c06/COPD-18-1995-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bba9/10503524/6a8be5db1f6c/COPD-18-1995-g0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bba9/10503524/a7ad489234d5/COPD-18-1995-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bba9/10503524/10f25d0a8674/COPD-18-1995-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bba9/10503524/828c5deecae0/COPD-18-1995-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bba9/10503524/b94de2ab7384/COPD-18-1995-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bba9/10503524/7fde117f716c/COPD-18-1995-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bba9/10503524/ca5862ac8c06/COPD-18-1995-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bba9/10503524/6a8be5db1f6c/COPD-18-1995-g0007.jpg

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