» Articles » PMID: 35004856

Identification of Diagnostic Markers Correlated With HIV Immune Non-response Based on Bioinformatics Analysis

Overview
Specialty Biology
Date 2022 Jan 10
PMID 35004856
Authors
Affiliations
Soon will be listed here.
Abstract

HIV-infected immunological non-responders (INRs) are characterized by their inability to reconstitute CD4 T cell pools after antiretroviral therapy. The risk of non-AIDS-related diseases in INRs is increased, and the outcome and prognosis of INRs are inferior to that of immunological responders (IRs). However, few markers can be used to define INRs precisely. In this study, we aim to identify further potential diagnostic markers associated with INRs through bioinformatic analyses of public datasets. This study retrieved the microarray data sets of GSE106792 and GSE77939 from the Gene Expression Omnibus (GEO) database. After merging two microarray data and adjusting the batch effect, differentially expressed genes (DEGs) were identified. Gene Ontology (GO) resource and Kyoto Encyclopedia of Genes and Genomes (KEGG) resource were conducted to analyze the biological process and functional enrichment. We performed receiver operating characteristic (ROC) curves to filtrate potential diagnostic markers for INRs. Gene Set Enrichment Analysis (GSEA) was conducted to perform the pathway enrichment analysis of individual genes. Single sample GSEA (ssGSEA) was performed to assess scores of immune cells within INRs and IRs. The correlations between the diagnostic markers and differential immune cells were examined by conducting Spearman's rank correlation analysis. Subsequently, miRNA-mRNA-TF interaction networks in accordance with the potential diagnostic markers were built with Cytoscape. We finally verified the mRNA expression of the diagnostic markers in clinical samples of INRs and IRs by performing RT-qPCR. We identified 52 DEGs in the samples of peripheral blood mononuclear cells (PBMC) between INRs and IRs. A few inflammatory and immune-related pathways, including chronic inflammatory response, T cell receptor signaling pathway, were enriched. FAM120AOS, LTA, FAM179B, JUN, PTMA, and SH3YL1 were considered as potential diagnostic markers. ssGSEA results showed that the IRs had significantly higher enrichment scores of seven immune cells compared with IRs. The miRNA-mRNA-TF network was constructed with 97 miRNAs, 6 diagnostic markers, and 26 TFs, which implied a possible regulatory relationship. The six potential crucial genes, FAM120AOS, LTA, FAM179B, JUN, PTMA, and SH3YL1, may be associated with clinical diagnosis in INRs. Our study provided new insights into diagnostic and therapeutic targets.

Citing Articles

Prognostic value of RRM1 and its effect on chemoresistance in pancreatic cancer.

Lin X, Tan Y, Pan L, Tian Z, Lin L, Su M Cancer Chemother Pharmacol. 2023; 93(3):237-251.

PMID: 38040978 DOI: 10.1007/s00280-023-04616-6.


SH3YL1 Protein Predicts Renal Outcomes in Patients with Type 2 Diabetes.

Han S, Han S, Ghee J, Cha J, Kang Y, Cha D Life (Basel). 2023; 13(4).

PMID: 37109492 PMC: 10141384. DOI: 10.3390/life13040963.


Identification of Potential Diagnostic Genes of HIV-Infected Immunological Non-Responders on Bioinformatics Analysis.

Ding Y, Pu C, Zhang X, Tang G, Zhang F, Yu G J Inflamm Res. 2023; 16:1555-1570.

PMID: 37082297 PMC: 10112482. DOI: 10.2147/JIR.S396055.


FDCSP Is an Immune-Associated Prognostic Biomarker in HPV-Positive Head and Neck Squamous Carcinoma.

Wu Q, Shao T, Huang G, Zheng Z, Jiang Y, Zeng W Biomolecules. 2022; 12(10).

PMID: 36291667 PMC: 9599724. DOI: 10.3390/biom12101458.


Is a Novel Prognostic-Related Biomarker in Glioma Correlating with Immune Infiltrates and Response to Oxidative Stress by Temozolomide.

Chen Z, Cui S, Dai Y, Lu C, Zhang H, Zhao W Oxid Med Cell Longev. 2022; 2022:7595230.

PMID: 36193074 PMC: 9526613. DOI: 10.1155/2022/7595230.

References
1.
Gazzola L, Tincati C, Bellistri G, Monforte A, Marchetti G . The absence of CD4+ T cell count recovery despite receipt of virologically suppressive highly active antiretroviral therapy: clinical risk, immunological gaps, and therapeutic options. Clin Infect Dis. 2009; 48(3):328-37. DOI: 10.1086/595851. View

2.
Moore R, Keruly J . CD4+ cell count 6 years after commencement of highly active antiretroviral therapy in persons with sustained virologic suppression. Clin Infect Dis. 2007; 44(3):441-6. DOI: 10.1086/510746. View

3.
Martin-Jaular L, Nevo N, Schessner J, Tkach M, Jouve M, Dingli F . Unbiased proteomic profiling of host cell extracellular vesicle composition and dynamics upon HIV-1 infection. EMBO J. 2021; 40(8):e105492. PMC: 8047442. DOI: 10.15252/embj.2020105492. View

4.
Li J, Li Z, Zhao S, Song Y, Si L, Wang X . Identification key genes, key miRNAs and key transcription factors of lung adenocarcinoma. J Thorac Dis. 2020; 12(5):1917-1933. PMC: 7330310. DOI: 10.21037/jtd-19-4168. View

5.
Liu J, Hou Y, Sun L, Wang L, He Y, Zhou Y . High population-attributable fractions of traditional risk factors for non-AIDS-defining diseases among people living with HIV in China: a cohort study. Emerg Microbes Infect. 2021; 10(1):416-423. PMC: 7971336. DOI: 10.1080/22221751.2021.1894904. View