Abstract 4903: Multimodal therapy with a potent vaccine, metronomic cyclophosphamide and anti-PD-1 enhances immunotherapy of advanced tumors by increasing activation and clonal expansion of tumor infiltrating T cells
Bibliographic record
Abstract
Abstract Future cancer immunotherapies will combine multiple treatments to improve immune responses to cancer through synergistic, multi-modal mechanisms. In Phase 1 and 1b clinical trials, we found that metronomic cyclophosphamide (mCPA; 50 mg BID) enhanced the immunogenicity of a DepoVaxTM (DPX) based cancer vaccine (DPX-Survivac) in ovarian cancer patients. We reproduced these results in preclinical transplantable tumor models which allowed us to study the underlying mechanisms of cyclophosphamide induced immune modulation, as well as explore additional combinations to enhance the therapeutic effect. Using a HPV-expressing murine tumor model (C3), we found that treatment with mCPA (20 mg/kg/day PO) in combination with a DPX peptide vaccine caused selective enrichment of antigen-specific CD8+ T cells, resulting in increased immune responses detected by IFN-ã ELISPOT and in vivo cytotoxicity assay. The combination provided long term-control of tumors when initiated within one week of tumor implantation, however efficacy was limited in mice bearing advanced tumors. Antigen-specific CD8+ T cells could be detected infiltrating advanced tumors by flow cytometry, along with increased expression of PD-1 on the T cells and PD-L1 on the tumor cells, suggesting that the tumor microenvironment (TME) was mediating immune suppression through increased PD-1:PD-L1 signaling. Treatment of tumor bearing mice with vaccine, mCPA and PD-1 blockade (with anti-PD-1 or anti-PD-L1) resulted in tumor control of established tumors which were not successfully treated with antibody monotherapy. Analysis of tumor infiltrating leukocytes by flow cytometry demonstrated that anti-PD-1 treatment did not further enhance tumor infiltration with antigen-specific CD8+ T cells induced by the vaccine/ mCPA treatment. However, RT-qPCR analysis of the tumor detected an increase in expression of cytotoxic T cell gene signatures within the tumor in combination with anti-PD-1 treatment. Clonal analysis was performed of the total TCRâ sequences using gDNA extracted from the tumors. Vaccine and mCPA treatment resulted in selective expansion of clones, as the top 10 clones accounted for 35% of the total TCRâ sequences; tri-therapy including anti-PD-1 significantly enhanced the expansion of T cells within the TME so that the top 10 clones accounted for 46% of the total TCRâ sequences (p<0.05). We conclude that anti-PD-1 therapy can enhance the efficacy of vaccine immunotherapy by promoting the activity and expansion of antigen-specific T cells within the TME. These results provide a rationale for clinical testing of checkpoint blockade therapy in combination with our highly immunogenic combination of mCPA and DPX-Survivac. Assessment of T cell clonality within the tumor may be an important biomarker for immunomodulatory treatments. Citation Format: Genevieve Weir, Olga Hrytsenko, Tara Quinton, Mohan Karkada, Neil L. Berinstein, Marianne Stanford, Marc Mansour. Multimodal therapy with a potent vaccine, metronomic cyclophosphamide and anti-PD-1 enhances immunotherapy of advanced tumors by increasing activation and clonal expansion of tumor infiltrating T cells. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4903.
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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".