Lee SY, Choi BS, Yoon CH, Kang C, Kim K, Kim KC. Selection of biomarkers for HIV-1 latency by integrated analysis.
Genomics 2018;
111:327-333. [PMID:
29454027 DOI:
10.1016/j.ygeno.2018.02.007]
[Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2017] [Revised: 02/08/2018] [Accepted: 02/12/2018] [Indexed: 01/10/2023]
Abstract
A major obstacle in the treatment of human immunodeficiency virus type 1 (HIV-1) is its ability to establish latent infection. To find novel biomarkers associated with the mechanism of HIV-1 latent infection, we identified 70 candidate genes in HIV-1 latently infected cells through the integrated analysis in a previous study. It is important to select more effective biomarkers among 70 candidates and to verify the possibility of selected biomarkers for HIV-1 latency. We identified the 24 and 25 genes from 70 candidate genes in significantly enriched categories selected by Database for Annotation, Visualization and Integrated Discovery (DAVID) software and Gene Set Enrichment Analysis (GSEA) software, respectively. Also, we investigated genes regulated in both HIV-1 latently infected cell lines and PBMCs from HIV-1 infected patients and found the genes with a common pattern of expression levels in both cell lines and PBMCs. Consequently, we identified nine genes, APBB2, GMPR, IGF2BP3, LRP1, MAD2L2, MX1, OXR1, PTK2B, and TNFSF13B, via integrated analysis. Especially, APBB2 and MAD2L2 were identified in both DAVID and GSEA software. Our findings suggest that nine genes were identified via integrated analysis as potential biomarkers and in particular, APBB2 and MAD2L2 may be considered as more significant biomarkers for HIV-1 latency.
Collapse