Virus-like vesicles expressing multiple antigens for immunotherapy of chronic hepatitis B
Bibliographic record
Abstract
ABSTRACT Infection with hepatitis B virus (HBV) can initiate chronic hepatitis and liver injury, eventually progressing to liver fibrosis or cancer and causing more than 600,000 deaths each year worldwide. Current treatments for chronic hepatitis B, relying on nucleoside antivirals and interferon, are inadequate and leave an unmet need for immunotherapeutic approaches. This report describes virus-like vesicles (VLV), a form of self-amplifying RNA replicons, which express multiple HBV antigens (polymerase, core, and middle surface) from a single vector (HBV-VLV). The HBV-VLV induces HBV-specific T cell responses to all three HBV antigens. Immunization of naive mice with the multiantigen HBV-VLV renders them resistant to acute challenge with HBV delivered by adeno-associated virus (AAV). Using a chronic model of HBV infection by AAV delivery of HBV, we demonstrate immunotherapeutic potential of the multiantigen HBV-VLV in combination with DNA booster immunization, as 40% of the HBV-VLV-treated mice showed a decline of the serum HBV surface antigen below the detection limit and marked reduction in liver HBV RNA accompanied by induction of HBsAg-specific CD8 T cells. These results warrant further evaluation of multiantigen HBV-VLV for immunotherapy of chronic hepatitis B. IMPORTANCE More than 240 million people worldwide are chronically infected with hepatitis B virus. Current therapies are not sufficiently effective and are often beyond reach in the developing world. We describe a virus-like vesicle-based immunotherapeutic vaccine that expresses three major antigens of hepatitis B virus as a self-amplifying RNA replicon. By incorporating three HBV antigens in a single vaccine, we ensure broad T cell responses. We demonstrate that immunization with this vaccine protects mice from hepatitis B virus in a model of acute challenge. Importantly, treatment with this vaccine shows 40% efficacy in a mouse model of chronic hepatitis B. Thus, this study paves the way for evaluation of the multi-antigen virus-like vesicles as a tool for immunotherapy of chronic hepatitis B.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".