Anders Sönnerborg

There is no cure of HIV infection due to latent intact HIV in cellular reservoirs, mainly in resting CD4+ cells. Several latency reversing agents (LRA) have been identified but no reduction in the reservoirs has been achieved in vivo. We screened a CRISPR-CAS knockout library targeting 2.000 drugable human genes and identified several novel genes maintaining HIV latency including C-terminal Src kinase (CSK). When inhibiting CSK, reactivation of latent HIV was seen in vitro. We will now further investigate the therapeutic potential of novel LRAs using state-of-the-art model systems. Our plan includes i) CRISPR-CAS screening for more druggable targets that reverse latency in GKO reporter virus infected Jurkat and primary human T cells

ii) identification of novel LRAs aand testing of small molecule inhibitors, including the CSK inhibitor

iii) testing selected LRAs on primary CD4+ T-cells from patients with suppressive viremia, assessing the reactivation of the replication competent reservoir and iv) in a subset of patients correlate variations in the reactivation potential to the integration sites in eu- or heterochromatin of the proviral HIV DNA. Our novel assays and approaches in HIV latency research will facilitate the identification for novel efficient LRAs and open new pathways towards functional HIV cure.

Current HIV cure trials primarily focus on people living with HIV (PLWH) who started antiretroviral therapy (ART) during the primary infection stage, as they are known to have smaller HIV reservoirs. However, there is a substantial knowledge gap regarding the size of the HIV reservoir in majority of PLWH. Our study aims to address this gap by exploring the size of the HIV reservoir through comprehensive clinical, immunological, and virological assessments, and by developing an algorithm to predict HIV reservoir size.To achieve this, the CHART-C study will include 200 PLWH on long-term successful ART, with a substudy examining the HIV reservoir in the central nervous system of 20 participants. We will use advanced assays such as IPDA, CADseq method, and quantification of HIV-specific humoral/cellular responses. Machine learning techniques will be employed to develop an algorithm to identify individuals with the smallest HIV reservoirs.The outcome of this study will be a clinical algorithm designed to select individuals with the smallest HIV reservoirs, thereby optimizing the inclusion criteria for future HIV cure trials and enhancing the potential for therapeutic success. Additionally, we will prepare for an analytical treatment interruption  HIV cure trial using two long-acting broadly neutralizing antibodies. The CHART-C trial aims to make a significant contribution to global HIV cure strategies and position Swedish HIV research at the forefront of this critical field.