Abstract 2836: Metronomic cyclophosphamide enhances antitumor immune response induced by a DepoVaxTM-based peptide vaccine.
Bibliographic record
Abstract
Abstract Advanced cancers utilize several mechanisms to escape immune-mediated detection and destruction thus reducing the effectiveness of cancer therapeutics on multiple levels. Low dose cyclophosphamide (CPA) has been investigated as an immune modulator to potentiate active immune response towards tumor cells, but a single bolus injection of CPA has been ineffective at boosting response to cancer vaccines in most clinical trials. We sought to determine if a metronomic regimen of low dose CPA (mCPA) could enhance the efficacy of a peptide-based vaccine formulated in DepoVaxTM (DPX). DPX is a novel vaccine platform comprised of liposomes in oil that is formulated with an adjuvant, universal T-helper peptide and specific tumor peptide antigens. Using a murine tumor model (C3) we tested the benefit of combining mCPA and vaccination for controlling well established subcutaneous solid tumors in vivo. Mice were treated starting 5 days after C3 tumor implantation with mCPA administered in drinking water in a one week on/ off schedule and vaccinated every 3 weeks. In this model, neither mCPA nor vaccine treatments alone were sufficient to eradicate advanced tumors. However, combining mCPA with vaccination provided effective tumor control. Ex vivo analysis of immune response after a single treatment of mCPA combined with vaccine showed a significant increase in antigen-specific IFN-γ release by ELISPOT, which became more pronounced after multiple rounds of treatment in tumor bearing mice. This immune response was accompanied by a corresponding increase in antigen-specific cytotoxic T cell activity as measured by in vivo CTL assay. Dextramer analysis of the antigen-specific CD8+ T cells in the vaccine-draining lymph node revealed that while the total number of CD8+ T cells decreased with mCPA treatment, the number of antigen-specific CD8+ T cells was increased by vaccination and not reduced by mCPA. Flow cytometric analysis of splenocyte cell populations did not show any significant reduction in CD4+CD25hiFoxP3+Treg populations due to mCPA treatment, as previously reported by others, but we did find an increase in myeloid-derived suppressor cells due to mCPA treatment that was decreased in mice treated with both mCPA & vaccination. Finally, adoptive transfer of T cells from tumor bearing mice treated with mCPA & vaccination significantly reduced tumor growth in tumor challenged recipients. Overall, our data indicate that mCPA combines with a peptide based DPX vaccine to enhance the T cell response to antigen that ultimately results in an improved immunotherapy for cancer. The immune-enhancing effects of mCPA in this model are multi-faceted and augment the T cell responses independent of direct cytotoxic effects on the tumor. The results of this pre-clinical study have assisted in the designing of a phase II clinical trial for DPX-Survivac vaccine in combination with mCPA in ovarian cancer patients. Citation Format: Genevieve M. Weir, Marianne M. Stanford, Neil L. Berinstein, Mohan Karkada, Robert S. Liwski, Marc Mansour. Metronomic cyclophosphamide enhances antitumor immune response induced by a DepoVaxTM-based peptide vaccine. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2836. doi:10.1158/1538-7445.AM2013-2836
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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) | 0.002 | 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".