A Recombinant Modified Vaccinia Ankara Vaccine Encoding Epstein–Barr Virus (EBV) Target Antigens: A Phase I Trial in UK Patients with EBV-Positive Cancer
Bibliographic record
Abstract
PURPOSE: Epstein-Barr virus (EBV) is associated with several cancers in which the tumor cells express EBV antigens EBNA1 and LMP2. A therapeutic vaccine comprising a recombinant vaccinia virus, MVA-EL, was designed to boost immunity to these tumor antigens. A phase I trial was conducted to demonstrate the safety and immunogenicity of MVA-EL across a range of doses. EXPERIMENTAL DESIGN: Sixteen patients in the United Kingdom (UK) with EBV-positive nasopharyngeal carcinoma (NPC) received three intradermal vaccinations of MVA-EL at 3-weekly intervals at dose levels between 5 × 10(7) and 5 × 10(8) plaque-forming units (pfu). Blood samples were taken at screening, after each vaccine cycle, and during the post-vaccination period. T-cell responses were measured using IFNγ ELISpot assays with overlapping EBNA1/LMP2 peptide mixes or HLA-matched epitope peptides. Polychromatic flow cytometry was used to characterize functionally responsive T-cell populations. RESULTS: Vaccination was generally well tolerated. Immunity increased after vaccination to at least one antigen in 8 of 14 patients (7/14, EBNA1; 6/14, LMP2), including recognition of epitopes that vary between EBV strains associated with different ethnic groups. Immunophenotypic analysis revealed that vaccination induced differentiation and functional diversification of responsive T-cell populations specific for EBNA1 and LMP2 within the CD4 and CD8 compartments, respectively. CONCLUSIONS: MVA-EL is safe and immunogenic across diverse ethnicities and thus suitable for use in trials against different EBV-positive cancers globally as well as in South-East Asia where NPC is most common. The highest dose (5 × 10(8) pfu) is recommended for investigation in current phase IB and II trials.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".