Boosting of CAR-T cells with rhabdovirus is limited by type I interferon and rapid contraction
Bibliographic record
Abstract
Abstract Rhabdovirus vaccines that encode tumour-associated antigens are potent boosting agents for adoptively transferred tumour-specific T cells. Employing rhabdovirus vaccines to boost adoptively transferred T cells relies on a priori knowledge of tumour epitopes, isolation of matched epitope-specific T cells, and a personalized vaccine, which limit clinical feasibility. Here, we investigated a universal strategy for boosting transferred tumour-specific T cells where boosting is provided through a chimeric antigen receptor (CAR) that is paired with a vesicular stomatitis virus (VSV) vaccine encoding the CAR-target. Boosting CAR-engineered tumour-specific T cells with paired VSV vaccines was associated with robust T cell expansion and delayed tumour progression in syngeneic models. CAR-T cell expansion and anti-tumour function was enhanced by blocking IFNAR1. However, vaccine-boosted CAR-T cells rapidly contracted and antigen-positive tumours re-emerged. In contrast, when the same T cells were boosted with VSV encoding antigen that stimulates through the TCR, the adoptively transferred T cells displayed improved persistence, tumour-specific endogenous cells expanded in parallel, and tumour cells carrying the antigen target were completely eradicated. Our findings underscore the need for further research into CAR-mediated boosting, how this differs mechanistically from TCR-mediated boosting, and the importance of engaging endogenous tumour-reactive T cells to achieve long-term tumour control.
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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 | 0.001 |
| 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".