ArticleAIDS patient care and STDs2016
Engineering HIV-Specific Immunity with Chimeric Antigen Receptors.
Article in AIDS patient care and STDs, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 15 citations in OpenAlex.
- NK cell immunotherapy after analytic treatment interruption is associated with HIV viral control.Molecular therapy. Advances · 2026Article
- Multiplex engineering of rhesus macaque NK cells enhances homing to sites of HIV replication in B cell follicles.bioRxiv : the preprint server for biology · 2026Article
- NK cell immunotherapy administered at the time of HIV recrudescence is associated with viral control.bioRxiv : the preprint server for biology · 2025Article
- Engineered Zinc Finger Protein Targeting 2LTR Inhibits HIV Integration in Hematopoietic Stem and Progenitor Cell-Derived Macrophages: In Vitro Study.International journal of molecular sciences · 2022Article
- Genetic in vivo engineering of human T lymphocytes in mouse models.Nature protocols · 2021Article
- The Use of the Humanized Mouse Model in Gene Therapy and Immunotherapy for HIV and Cancer.Frontiers in immunology · 2018Review
- Simian Immunodeficiency Virus (SIV)-Specific Chimeric Antigen Receptor-T Cells Engineered to Target B Cell Follicles and Suppress SIV Replication.Frontiers in immunology · 2018Article
- In Vivo Murine-Matured Human CD3Molecular therapy. Methods & clinical development · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
HIV remains a highly important public health and clinical issue despite many recent advances in attempting to develop a cure, which has remained elusive for most people infected with HIV. HIV disease can be controlled with pharmacologic therapies; however, these treatments are expensive, may have severe side effects, and are not curative. Consequently, an improved means to control or eliminate HIV replication is needed. Cytotoxic T lymphocytes (CTLs) play a critical role in controlling viral replication and are an important part in the ability of the immune response to eradicate most viral infections. There are considerable efforts to enhance CTL responses in HIV-infected individuals in hopes of providing the immune response with armaments to more effectively control viral replication. In this review, we discuss some of these efforts and focus on the development of a gene therapy-based approach to engineer hematopoietic stem cells with an HIV-1-specific chimeric antigen receptor, which seeks to provide an inexhaustible source of HIV-1-specific immune cells that are MHC unrestricted and superior to natural antiviral T cell responses. These efforts provide the basis for further development of T cell functional enhancement to target and treat chronic HIV infection in hopes of eradicating the virus from the body.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.