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Record W2622458078 · doi:10.1128/jvi.00634-17

Comprehensive Cross-Clade Characterization of Antibody-Mediated Recognition, Complement-Mediated Lysis, and Cell-Mediated Cytotoxicity of HIV-1 Envelope-Specific Antibodies toward Eradication of the HIV-1 Reservoir

2017· article· en· W2622458078 on OpenAlexafffund
Shariq Mujib, Jun Liu, A. K. M. Nur-ur Rahman, J. Schwartz, Phil Bonner, Feng Yun Yue, Mario Ostrowski

Bibliographic record

VenueJournal of Virology · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
FundersCanadian Institutes of Health ResearchGovernment of Canada
KeywordsAntibody-dependent cell-mediated cytotoxicityAntibodyBiologyVirologyImmune systemHIV vaccineImmunologyCytotoxicityIn vitroVaccine trialMonoclonal antibodyBiochemistry

Abstract

fetched live from OpenAlex

ABSTRACT Immunotherapy with passive administration of broadly neutralizing HIV-1 envelope-specific antibodies (bnAbs) in the setting of established infectionin vivohas yielded mixed results. The contribution of different antibodies toward the direct elimination of infected cells is poorly understood. In this study, we determined the ability of 12 well-characterized anti-HIV-1 neutralizing antibodies to recognize and eliminate primary CD4 T cells infected with HIV-1 belonging to clades A, B, C, and D, via antibody-dependent complement-mediated lysis (ADCML) and antibody-dependent cell-mediated cytotoxicity (ADCC),in vitro. We further tested unique combinations of these antibodies to determine the optimal antibody cocktails to be tested in future clinical trials. We report that antibody binding to infected CD4 T cells is highly variable and correlates with ADCML and ADCC processes. Particularly, antibodies targeting the envelope glycan shield (2G12) and V1/V2 site (PG9, PG16, and PGT145) are best at recognizing HIV-1-infected CD4 T cells. However, only PG9 and PG16 and their combinations with other bnAbs sufficiently induced the elimination of HIV-1-infected CD4 T cells by ADCML, ADCC, or both. Notably, CD4 binding site antibodies VRC01, 3BNC117, and NIH45-46 G54W did not exhibit recognition of infected cells and were unable to induce their killing. Future trials geared toward the development of a cure for HIV/AIDS should incorporate V1/V2 antibodies for maximal clearance of infected cells. With the use of only primary immune cells, we conducted a comprehensive cross-clade physiological analysis to aid the direction of antibodies as therapeutics toward the development of a cure for HIV/AIDS. IMPORTANCESeveral antibodies capable of neutralizing the majority of circulating HIV-1 strains have been identified to date and have been shown to prevent infection in animal models. However, the use of combinations of such broadly neutralizing antibodies (bnAbs) for the treatment and eradication of HIV-1 in infected humans remains uncertain. In this study, we tested the ability of bnAbs to directly recognize and eliminate primary human CD4 T cells infected with diverse HIV-1 strains representative of the global epidemic by antibody-dependent pathways. We also tested several combinations of bnAbs in our assays in order to maximize the clearance of infected cells. We show that the ability of bnAbs to identify and kill infected cells is highly variable and that only a few of them are able to exert this function. Our data will help guide the formulation of bnAbs to test in future human trials aimed at the development of a cure.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.303
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations38
Published2017
Admission routes2
Has abstractyes

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