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Analysis of Key miRNA/mRNA Functional Axes During Host Dendritic Cell Immune Response to Mycobacterium tuberculosis Based on GEO Datasets
Analysis of Key miRNA/mRNA Functional Axes During Host Dendritic Cell Immune Response to Mycobacterium tuberculosis Based on GEO Datasets
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Analysis of Key miRNA/mRNA Functional Axes During Host Dendritic Cell Immune Response to Mycobacterium tuberculosis Based on GEO Datasets
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Analysis of Key miRNA/mRNA Functional Axes During Host Dendritic Cell Immune Response to Mycobacterium tuberculosis Based on GEO Datasets
Analysis of Key miRNA/mRNA Functional Axes During Host Dendritic Cell Immune Response to Mycobacterium tuberculosis Based on GEO Datasets

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Analysis of Key miRNA/mRNA Functional Axes During Host Dendritic Cell Immune Response to Mycobacterium tuberculosis Based on GEO Datasets
Analysis of Key miRNA/mRNA Functional Axes During Host Dendritic Cell Immune Response to Mycobacterium tuberculosis Based on GEO Datasets
Journal Article

Analysis of Key miRNA/mRNA Functional Axes During Host Dendritic Cell Immune Response to Mycobacterium tuberculosis Based on GEO Datasets

2025
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Overview
Background: Dendritic cells (DCs) play an important role as a bridge between innate and adaptive immunity, and changes in gene expression of DCs during the immune response to Mycobacterium tuberculosis (M.tb) may affect the development of tuberculosis. Methods: Using systems biology methods, mRNA and miRNA expression profile data of DCs infected with M.tb were obtained. A total of 1398 differentially expressed mRNAs and 79 differentially expressed miRNAs were identified, and a corresponding miRNA–mRNA regulatory network was constructed using Cytoscape 3.9.1 software. The functional annotations and pathway classifications of the miRNA–mRNA network were identified using the DAVID tool. Then, the key pathway modules in the miRNA–mRNA network were screened and subjected to PPI network analysis to identify hub nodes. Subsequently the miRNA/mRNA axis was determined, validated by qRT-PCR, and evaluated through ROC curve analysis. Results: The TNF signaling pathway and the Tuberculosis pathway were key pathway modules, with miR-34a-3p/TNF and miR-190a-3p/IL1B being the greatest correlations with the two pathway modules. qRT-PCR results showed that IL1B and miR-190a-3p exhibited significant differences in both the H37Ra and BCG infection groups. The AUC of two factors (IL1B and miR-190a-3p) was 0.9561 and 0.9625, respectively, showing high sensitivity and specificity. Conclusions: Consequently, miR-190a-3p/IL1B might be a good candidate marker to characterize the immune response of DCs to M.tb and a transition signal from innate to adaptive immunity.

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