Abstract 752: A CCR4 antagonist combined with protein-or DNA-based vaccines efficiently breaks tolerance and elicits CD8+T cells directed against self and viral associated tumor antigens
Bibliographic record
Abstract
Abstract Regulatory T cells (Treg) may impede vaccine efficacy in cancer. CCR4 antagonists, an emergent class of Treg inhibitor, have been shown to block recruitment of Treg into lymph node mediated by CCL17 and CCL22. As most tumor antigens are self antigens possibly controled by Treg, our aim was to demonstrate the ability of a CCR4 antagonist to induce CD8+T cells directed against various self tumor antigens. For this purpose we selected various transgenic mice expressing Her2/neu, E7 or OVA as self antigen. Protein based vaccine vectorized or not by the B subunit of Shiga toxin (a vector targeting dendritic cells) and a DNA based vaccine coding for the E7 protein derived from HPV were included in this study and tested in combination or not with the CCR4 antagonist. Induction of functional anti-self CD8+T cells could be observed against various model self antigens (Her2/neu, E7, OVA) only when protein (delivered via the B subunit of Shiga toxin) – or DNA-based vaccines were combined with the CCR4 antagonist. Antigen specific CD8+T cells were detected by Tetramer and Elispot assays. This strategy to block Treg was more efficient than cyclophosphamide and similar to the depletion of Treg by anti-CD25 mAb.However compared to mAb, the CCR4 antagonist has a short life time which may avoid potential autoimmune complication caused by long term blockade of Treg. In contrast to anti-CD25mAb and cyclophosphamide, the CCR4 antagonist did not modify the number or the percent of peripheral Treg. As only 20% of Treg in mice expressed CCR4, we further characterized this population and showed that it corresponded to memory (CC44high) activated (ICOS+) cells. Activation of CCR4 negative Treg led to upregulation of CCR4 on these cells. Since the targeting of only 20% of Treg expressing CCR4 was sufficient to break tolerance mediated by Treg, these results strongly suggest that these CCR4+Tregs represent an important population to be targeted to modulate T reg activity. In human, we showed that CCR4 is expressed by more than 70% of peripheral or intra-lymph node Treg. The previous demonstration that a CCR4 antagonist is efficient to block human Treg, together with the high expression of CCR4 in human Treg also provide some rationale to develop this new class of Treg inhibitor in human.Our vaccine combining an efficient antigen delivery system which targets dendritic cells (the B subunit of Shiga toxin) to a CCR4 antagonist able to break tolerance mediated by Treg during the priming phase may thus represent a prototype cancer vaccine to elicit potent functional anti-tumor CD8+T cells in the context of immunosuppression mediated by Treg in cancer patients Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 752. doi:10.1158/1538-7445.AM2011-752
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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) | 0.003 | 0.001 |
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".