Ding Yanhong, Pu Cheng, Zhang Xiao, Tang Gaoyan, Zhang Fengjuan, Yu Guohua
Department of Medical Oncology, the First Affiliated Hospital of Weifang Medical University, Weifang, 261032, People's Republic of China.
Key Laboratory of Animal Disease and Human Health of Sichuan Province, College of Veterinary Medicine, Sichuan Agricultural University, Wenjiang District, 611130, People's Republic of China.
J Inflamm Res. 2023 Apr 14;16:1555-1570. doi: 10.2147/JIR.S396055. eCollection 2023.
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.
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.
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.
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.
尽管病毒载量检测不到,但感染HIV的免疫无应答者(INR)的CD4 T细胞计数未能恢复正常。INR发生获得性免疫缺陷综合征(AIDS)临床进展和非AIDS事件的风险增加,死亡率高于免疫应答者(IR)。本研究旨在发现有助于区分INR与IR的基因,并探索INR的可能机制。
使用GEO微阵列数据集GSE143742筛选INR与IR之间的差异表达基因(DEG)。使用基因本体论(GO)和京都基因与基因组百科全书(KEGG)分析研究DEG的生物学功能。将DEG与加权基因共表达网络分析(WGCNA)链接的模块进行交叉,以找到共同基因。使用支持向量机-递归特征消除(SVM-RFE)和套索回归模型鉴定关键基因。使用GEO数据库数据集GSE106792进行ROC分析,以评估关键基因的诊断有效性。Cytoscape为诊断基因创建了一个miRNA-mRNA-转录因子(TF)网络。CIBERSORT和流式细胞术检测INR和IR的免疫微环境。在10例INR和10例IR临床样本中,通过逆转录定量聚合酶链反应(RT-qPCR)和蛋白质免疫印迹法验证诊断基因的表达。
我们在INR组和IR组之间获得了190个DEG。功能富集分析发现线粒体和凋亡相关途径有显著富集。CD69和锌指蛋白207(ZNF207)被鉴定为潜在的诊断基因。在miRNA-mRNA-TF网络中,CD69和ZNF207共享一个转录因子核受体辅阻遏物1(NCOR1)。CIBERSORT进行的免疫微环境分析表明,与INR相比,IR的静息记忆CD4 T细胞水平较高,活化记忆CD4 T细胞和静息树突状细胞水平较低,流式细胞术分析证实了这一点。此外,CD69和ZNF207与免疫细胞相关。实验证实了诊断基因在INR和IR中的表达。
CD69和ZNF207被鉴定为区分INR与IR的潜在诊断基因。我们的研究结果为INR的诊断和治疗靶点提供了新线索。