Exploring Target Genes in the miRNA-mRNA Regulatory Network of Lung Adenocarcinoma Based on Bioinformatics

目的:本研究主要针对肺腺癌,旨在分析其组织中的差异表达基因,并探究miRNA-mRNA调控网络的关系,寻找潜在的分子靶点和治疗靶点。方法:通过下载GEO数据库中GSE74190和GSE140797数据,结合R语言进行数据分析,筛选出在两组芯片数据中具有差异表达的基因,即差异表达基因(differentially expressed genes, DGEs),作为后续研究的重点。对两组肺腺癌数据的DGEs进行miRNA-mRNA调控网络的构建,在CYTOSCAPE中进行可视化,得到关键调控网络与基因靶点,使用GEPIA2验证之前关键基因的表达与患者预后总生存率的关系。结果:miRNA-mRNA调控网络中显示有3个差异表达的miRNA基因均下调分别为hsa-miR-486-5p、hsa-miR-139-5p、hsa-miR-338-3p。在mRNA组中有7个差异表达基因,六个下调基因为DES、EMP2、COL6A6、PIK3R1、GDF10、LRRN3。一个上调基因为COL1A1。结论:探究差异miRNA在肺腺癌中通过调控下游靶向mRNA,建立miRNA-mRNA调控网络,使得我们对于肺腺癌中的基因调控机制更加深入了解,对肺腺癌中的生物学过程更加深入了解。本研究通过对关键miRNA-mRNA调控网络的构建,为肺腺癌的研究与治疗提供了新的靶点。Objective: To explore differentially expressed genes in lung adenocarcinoma tissue, study the relationship between miRNA-mRNA regulatory networks in lung adenocarcinoma, and identify potential molecular and therapeutic targets for lung adenocarcinoma. Method: Download samples from GEO, analyze data using R language based on GSE74190 and GSE140797 data and select genes with significant expression differences between the two sets of chip data, namely differentially expressed genes. Differently expressed genes (DGEs), and miRNA-mRNA regulatory networks were constructed on DGEs from two sets of lung adenocarcinoma data, visualized in CYTOSCAPE to obtain key regulatory networks and gene targets. GEPIA2 was used to validate the relationship between the expression of previous key genes and the overall survival rate of patients’ prognosis. Results: The results showed that three differentially expressed miRNA genes were downregulated in the miRNA-mRNA regulatory network, namely hsa-miR-486-5p, hsa-miR-139-5p, and hsa-miR-338-3p. There are 7 differentially expressed genes in the mRNA group, and six downregulated genes are DES, EMP2, COL6A6, PIK3R1, GDF10, and LRRN3. One upregulated gene is COL1A1. Conclusion: Exploring differential miRNAs in lung adenocarcinoma by regulating downstream targeted mRNA, and establishing a miRNA-mRNA regulatory network, enables us to have a deeper understanding of the gene regulatory mechanisms in lung adenocarcinoma and the biological processes in lung adenocarcinoma. This study provides new targets for the research and treatment of lung adenocarcinoma by constructing key miRNA-mRNA regulatory networks.

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Publication Details

Journal
Journal of Clinical Personalized Medicine
Published
2025-01-01
DOI
https://doi.org/10.12677/jcpm.2025.42294
Primary Topic
Cancer-related molecular mechanisms research
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article
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article

Exploring Target Genes in the miRNA-mRNA Regulatory Network of Lung Adenocarcinoma Based on Bioinformatics

刘梦 段
Journal of Clinical Personalized Medicine
Cancer-related molecular mechanisms research
article

Exploring Target Genes in the miRNA-mRNA Regulatory Network of Lung Adenocarcinoma Based on Bioinformatics

刘梦 段
article en

Abstract

目的:本研究主要针对肺腺癌,旨在分析其组织中的差异表达基因,并探究miRNA-mRNA调控网络的关系,寻找潜在的分子靶点和治疗靶点。方法:通过下载GEO数据库中GSE74190和GSE140797数据,结合R语言进行数据分析,筛选出在两组芯片数据中具有差异表达的基因,即差异表达基因(differentially expressed genes, DGEs),作为后续研究的重点。对两组肺腺癌数据的DGEs进行miRNA-mRNA调控网络的构建,在CYTOSCAPE中进行可视化,得到关键调控网络与基因靶点,使用GEPIA2验证之前关键基因的表达与患者预后总生存率的关系。结果:miRNA-mRNA调控网络中显示有3个差异表达的miRNA基因均下调分别为hsa-miR-486-5p、hsa-miR-139-5p、hsa-miR-338-3p。在mRNA组中有7个差异表达基因,六个下调基因为DES、EMP2、COL6A6、PIK3R1、GDF10、LRRN3。一个上调基因为COL1A1。结论:探究差异miRNA在肺腺癌中通过调控下游靶向mRNA,建立miRNA-mRNA调控网络,使得我们对于肺腺癌中的基因调控机制更加深入了解,对肺腺癌中的生物学过程更加深入了解。本研究通过对关键miRNA-mRNA调控网络的构建,为肺腺癌的研究与治疗提供了新的靶点。Objective: To explore differentially expressed genes in lung adenocarcinoma tissue, study the relationship between miRNA-mRNA regulatory networks in lung adenocarcinoma, and identify potential molecular and therapeutic targets for lung adenocarcinoma. Method: Download samples from GEO, analyze data using R language based on GSE74190 and GSE140797 data and select genes with significant expression differences between the two sets of chip data, namely differentially expressed genes. Differently expressed genes (DGEs), and miRNA-mRNA regulatory networks were constructed on DGEs from two sets of lung adenocarcinoma data, visualized in CYTOSCAPE to obtain key regulatory networks and gene targets. GEPIA2 was used to validate the relationship between the expression of previous key genes and the overall survival rate of patients’ prognosis. Results: The results showed that three differentially expressed miRNA genes were downregulated in the miRNA-mRNA regulatory network, namely hsa-miR-486-5p, hsa-miR-139-5p, and hsa-miR-338-3p. There are 7 differentially expressed genes in the mRNA group, and six downregulated genes are DES, EMP2, COL6A6, PIK3R1, GDF10, and LRRN3. One upregulated gene is COL1A1. Conclusion: Exploring differential miRNAs in lung adenocarcinoma by regulating downstream targeted mRNA, and establishing a miRNA-mRNA regulatory network, enables us to have a deeper understanding of the gene regulatory mechanisms in lung adenocarcinoma and the biological processes in lung adenocarcinoma. This study provides new targets for the research and treatment of lung adenocarcinoma by constructing key miRNA-mRNA regulatory networks.

Journal of Clinical Personalized MedicineVol. 04(02)
Openalex Percentile: Top 91%
Cancer-related molecular mechanisms research
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Exploring Target Genes in the miRNA-mRNA Regulatory Network of Lung Adenocarcinoma Based on Bioinformatics — 刘梦 段 · Journal of Clinical Personalized Medicine (2025) | TGRS Research Map | TGRS