Enhancing functional antibody responses against HIV envelope V1V2 through vaccine formulations
Bibliographic record
Abstract
Background: Despite decades of research, the development of an effective HIV vaccine remains a significant challenge. Recent findings from three large vaccine efficacy trials have identified antibodies against the V1V2 domain of the HIV envelope glycoprotein as a potential correlate of reduced infection risk, offering a promising avenue for improving vaccine efficacy. Vaccine-elicited anti-V1V2 antibodies do not mediate potent virus-neutralizing activities, but they mediate Fc-dependent effector functions. Methods: This study evaluated the capacity of V1V2-scaffold vaccines in different formulations to generate antibody responses with Fc-mediated functions. BALB/c mice were immunized with V1V2-scaffold proteins formulated with one of the following adjuvants: MF59-like squalene-based oil-in-water emulsion (Addavax), a combination of TLR7/8 and RIG-I agonists (IMDQ-PC/IVT), nanoemulsion and RIG-I agonist (NE/IVT), or empty lipid nanoparticles (eLNP). All formulations were administered intramuscularly except NE/IVT, which was given intranasally. For comparison, we also tested a V1V2-scaffold-expressing mRNA-LNP vaccine delivered intramuscularly and an Env gp140 protein with liposomal MPLA/DDA adjuvant administered subcutaneously. Results: Among the six vaccine formulations tested, V1V2-scaffold immunogens adjuvanted with LNP (eLNP and mRNA-LNP) elicited the most robust and cross-reactive serum IgG responses that recognized native Env on cell surfaces or virions. The eLNP and mRNA-LNP groups, along with IMDQ-PC/IVT, also elicited functional IgG2a, and correspondingly displayed Fc-mediated activities, as measured by antibody-dependent cellular phagocytosis and FcγRIV binding. Notably, IMDQ-PC/IVT elicited predominantly IgG2a with minimal IgG1, eLNP stimulated IgG1 and IgG2a with IgG1 dominance, whereas mRNA-LNP yielded more balanced IgG2a/IgG1 responses. Conclusions: Data from this study provide new insights into the utility of novel formulations for V1V2-scaffold immunogens as a strategy for optimizing the induction of functional V1V2-specific antibodies to improve HIV vaccine efficacy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".