Related Experiment Video
Updated: Aug 2, 2025
SILAC Based Proteomic Characterization of Exosomes from HIV-1 Infected Cells
Published on: March 3, 2017
Identification of Potential Diagnostic Genes of HIV-Infected Immunological Non-Responders on Bioinformatics Analysis
Yanhong Ding1, Cheng Pu2, Xiao Zhang3
1Department of Medical Oncology, the First Affiliated Hospital of Weifang Medical University, Weifang, 261032, People's Republic of China.
Purpose:
HIV-infected immunological non-responders (INRs) failed to achieve the normalization of CD4+ T cell counts despite their undetectable viral load. INRs have an increased risk of clinical progressions of Acquired Immunodeficiency Syndrome (AIDS) and non-AIDS events, accompanied by higher mortality rates than immunological responders (IRs). This study aimed to discover the genes, which help to distinguish INRs from IRs and explore the possible mechanism of INRs.
Methods:
Screening DEGs between INRs and IRs using GEO microarray dataset GSE143742. DEG biological functions were investigated using GO and KEGG analysis. DEGs and WGCNA linked modules were intersected to find common genes. Key genes were identified using SVM-RFE and LASSO regression models. ROC analysis was done to evaluate key gene diagnostic effectiveness using GEO database dataset GSE106792. Cytoscape created a miRNA-mRNA-TF network for diagnostic genes. CIBERSORT and flow cytometry examined the INRs and IRs immune microenvironments. In 10 INR and 10 IR clinical samples, diagnostic gene expression was verified by RT-qPCR and Western blot.
Results:
We obtained 190 DEGs between the INR group and IR group. Functional enrichment analysis found a significant enrichment in mitochondria and apoptosis-related pathways. CD69 and ZNF207 were identified as potential diagnostic genes. CD69 and ZNF207 shared a transcription factor, NCOR1, in the miRNA-mRNA-TF network. Immune microenvironment analysis by CIBERSORT showed that IRs had a higher level of resting memory CD4+ T cells, lower level of activated memory CD4+ T cells and resting dendritic cells than INRs, as confirmed by flow cytometry analysis. In addition, CD69 and ZNF207 were correlated with immune cells. Experiments confirmed the expression of the diagnostic genes in INRs and IRs.
Conclusion:
CD69 and ZNF207 were identified as potential diagnostic genes to discriminate INRs from IRs. Our findings offered new clues to diagnostic and therapeutic targets for INRs.
