{"title":"Eliminating the persistent HIV reservoir based on biomarker expression - How do we get there?","authors":"Nadejda Beliakova-Bethell","doi":"10.1016/j.virol.2024.110368","DOIUrl":null,"url":null,"abstract":"<p><p>Persistent HIV reservoir with different levels of proviral transcriptional activity represents a hurdle to HIV cure. The absence of a specific molecular signature or a \"biomarker\" to define cells latently infected with HIV limits reservoir eradication efforts. Biomarkers proposed in the literature define subsets of latently infected cells. This article discusses factors contributing to biomarker heterogeneity: external stimuli the cells are exposed to, tissue microenvironments, and person-to-person variation. Despite reservoir heterogeneity, several biomarkers, e.g., programmed cell death 1 and the Fc fragment of IgG low affinity IIa receptor, were reported consistently in multiple studies; however, they alone are unlikely to define all the HIV reservoir cells. Identifying a minimal set of cell surface proteins that together define all reservoir subsets is needed. Future studies will need to focus on the identification of co-expressed proteins that define the same sets of cells to reduce the number of proteins in a biomarker panel. A detailed characterization of tissue biomarkers and proteins expressed in latently infected cells of the myeloid lineage is needed to ensure that all the reservoirs are targeted throughout the body. Furthermore, the effect of underlying conditions that develop as people with HIV age on the manifestation of latency should be evaluated. With the development of novel technologies, such as spatial transcriptomics and proteomics, such endeavors will soon be possible. Thus, there is promise that a minimal set of proteins defining all the different reservoir subsets can be identified and developed into a reservoir targeting strategy.</p>","PeriodicalId":94266,"journal":{"name":"Virology","volume":"603 ","pages":"110368"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Virology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.virol.2024.110368","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Persistent HIV reservoir with different levels of proviral transcriptional activity represents a hurdle to HIV cure. The absence of a specific molecular signature or a "biomarker" to define cells latently infected with HIV limits reservoir eradication efforts. Biomarkers proposed in the literature define subsets of latently infected cells. This article discusses factors contributing to biomarker heterogeneity: external stimuli the cells are exposed to, tissue microenvironments, and person-to-person variation. Despite reservoir heterogeneity, several biomarkers, e.g., programmed cell death 1 and the Fc fragment of IgG low affinity IIa receptor, were reported consistently in multiple studies; however, they alone are unlikely to define all the HIV reservoir cells. Identifying a minimal set of cell surface proteins that together define all reservoir subsets is needed. Future studies will need to focus on the identification of co-expressed proteins that define the same sets of cells to reduce the number of proteins in a biomarker panel. A detailed characterization of tissue biomarkers and proteins expressed in latently infected cells of the myeloid lineage is needed to ensure that all the reservoirs are targeted throughout the body. Furthermore, the effect of underlying conditions that develop as people with HIV age on the manifestation of latency should be evaluated. With the development of novel technologies, such as spatial transcriptomics and proteomics, such endeavors will soon be possible. Thus, there is promise that a minimal set of proteins defining all the different reservoir subsets can be identified and developed into a reservoir targeting strategy.