Abstract 4405: Immune modulation and Treg suppression with metronomic cyclophosphamide enhances the anti-tumor effect of a therapeutic peptide vaccine in a murine model
Bibliographic record
Abstract
Abstract In order to be optimally effective therapeutic cancer vaccines must be combined with immune modulatory approaches, particularly in advanced cancer where several different pathways of cancer induced immune suppression may be active. We have developed a potent cancer vaccine enhancement formulation named DepoVaxTM (DPX) that is particularly well suited for the delivery of peptide antigens. DPX is a novel vaccine platform comprised of liposomes in oil that is formulated with a TLR adjuvant, universal T-helper peptide and specific tumor peptide antigens. We have shown that DPX generates better immune responses than Montanide based emulsion formulations. A major obstacle to any cancer vaccine, however, is tumor induced immune suppression. Regulatory T cell (Treg) mediated immune suppression is an important mechanism of tumor immune evasion in many types of cancer including ovarian cancer. We sought to determine if combining a DPX-based peptide vaccine approach with immune modulation in the form of Treg suppression could enhance the anti-tumor effect of the vaccine. Metronomic cyclophosphamide (mCPA) treatment has been reported to selectively sustain reduced regulatory T cell numbers and activity. Using a murine tumor model (C3) we tested the benefit of combining mCPA and DPX vaccination for controlling well established subcutaneous solid tumors in vivo. We found that neither mCPA or DPX treatments alone were sufficient to eradicate advanced C3 tumors. However, combining mCPA with DPX vaccination provided effective tumor control. We further characterized the immune response by isolating and phenotyping tumor infiltrating lymphocytes and testing their immunogenicity by IFN-γ ELISPOT assay. Our results indicate that the DPX vaccine can increase the levels of antigen-specific CD8+ T cells and mCPA treatment reduces the CD4+FoxP3+ T regulatory cells. We conclude that immune responses generated by the DPX vaccine were more effective at controlling advanced tumors together with reduced Treg-mediated immune suppression. We have designed and initiated a phase I/II clinical trial to test a DPX vaccine targeting Survivin (DPX-Survivac), in combination with mCPA in ovarian cancer patients. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4405. doi:1538-7445.AM2012-4405
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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 | 0.001 | 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".