Immunotherapy with Cell-Based Biological Drugs to Cure HIV-1 Infection.
Gabriel SiracusanoLopalco LuciaPublished in: Cells (2021)
Since its discovery 35 years ago, there have been no therapeutic interventions shown to enable full HIV-1 remission. Combined antiretroviral therapy (cART) has achieved the sustained control of HIV-1 replication, however, the life-long treatment does not eradicate long-lived latently infected reservoirs and can result in multiple side effects including the development of multidrug-resistant escape mutants. Antibody-based treatments have emerged as alternative approaches for a HIV-1 cure. Here, we will review clinical advances in coreceptor-targeting antibodies, with respect to anti-CCR5 antibodies in particular, which are currently being generated to target the early stages of infection. Among the Env-specific antibodies widely accepted as relevant in cure strategies, the potential role of those targeting CD4-induced (CD4i) epitopes of the CD4-binding site (CD4bs) in eliminating HIV-1 infected cells has gained increasing interest and will be presented. Together, with approaches targeting the HIV-1 replication cycle, we will discuss the strategies aimed at boosting and modulating specific HIV-1 immune responses, highlighting the harnessing of TLR agonists for their dual role as latency reverting agents (LRAs) and immune-modulatory compounds. The synergistic combinations of different approaches have shown promising results to ultimately enable a HIV-1 cure.
Keyphrases
- antiretroviral therapy
- hiv infected
- hiv positive
- human immunodeficiency virus
- hiv aids
- hiv infected patients
- hiv testing
- immune response
- men who have sex with men
- multidrug resistant
- hepatitis c virus
- cancer therapy
- stem cells
- small molecule
- toll like receptor
- south africa
- dendritic cells
- climate change
- drug delivery
- mesenchymal stem cells
- oxidative stress
- cell proliferation
- induced apoptosis
- inflammatory response
- deep learning
- high throughput
- physical activity
- cystic fibrosis
- endoplasmic reticulum stress
- gram negative
- machine learning
- human health