Metronomic cyclophosphamide enhances HPV16E7 peptide vaccine induced antigen-specific and cytotoxic T-cell mediated antitumor immune response
Bibliographic record
Abstract
In clinical trials, metronomic cyclophosphamide (CPA) is increasingly being combined with vaccines to reduce tumor-induced immune suppression. Previous strategies to modulate the immune system during vaccination have involved continuous administration of low dose chemotherapy, studies that have posed unique considerations for clinical trial design. Here, we evaluated metronomic CPA in combination with a peptide vaccine targeting HPV16E7 in an HPV16-induced tumor model, focusing on the cytotoxic T-cell response and timing of low dose metronomic CPA (mCPA) treatment relative to vaccination. Mice bearing C3 tumors were given metronomic CPA on alternating weeks in combination with immunization with a DepoVax vaccine containing HPV16E749–57 peptide antigen every 3 weeks. Only the combination therapy provided significant long-term control of tumor growth. The efficacy of the vaccine was uncompromised if given at the beginning or end of a cycle of metronomic CPA. Metronomic CPA had a pronounced lymphodepletive effect on the vaccine draining lymph node, yet did not reduce the development of antigen-specific CD8+ T cells induced by vaccination. This enrichment correlated with increased cytotoxic activity in the spleen and increased expression of cytotoxic gene signatures in the tumor. Immunity could be passively transferred through CD8+ T cells isolated from tumor-bearing mice treated with the combinatorial treatment regimen. A comprehensive survey of splenocytes indicated that metronomic CPA, in the absence of vaccination, induced transient lymphodepletion marked by a selective expansion of myeloid-derived suppressor cells. These results provide important insights into the multiple mechanisms of metronomic CPA induced immune modulation in the context of a peptide cancer vaccine that may be translated into more effective clinical trial designs.
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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".