Therapeutic vaccines and cancer: focus on DPX-0907
Bibliographic record
Abstract
In an attempt to significantly enhance immunogenicity of peptide cancer vaccines, we developed a novel non-emulsion depot-forming vaccine platform called DepoVax™ (DPX). Human leukocyte antigen (HLA)-A2 restricted peptides naturally presented by cancer cells were used as antigens to create a therapeutic cancer vaccine, DPX-0907. In a phase I clinical study, the safety and immune-activating potential of DPX-0907 in advanced-stage breast, ovarian, and prostate cancer patients were examined, following encouraging results in HLA-A2 transgenic mice. The DPX-0907 vaccine was shown to be safe and well tolerated, with injection-site reactions being the most commonly reported adverse event. Vaccinated cancer patients exhibited a 61% immune response rate, with higher response rates in the breast and ovarian cancer patient cohorts. In keeping with the higher immune efficacy of this vaccine platform, antigen-specific responses were detected in 73% of immune responders after just one vaccination. In 83% of responders, peptide-specific T-cells were detected at two or more time points post-vaccination, with 64% of these patients showing evidence of immune persistence. Immune monitoring also demonstrated the generation of antigen-specific T-cell memory, with the ability to secrete multiple type 1 cytokines. The novel DPX formulation promotes multifunctional effector/memory responses to peptide-based tumor-associated antigens. The data support the capacity of DPX-0907 to elicit type-1 biased immune responses, warranting further clinical development of the vaccine. In this review, we discuss the rationale for developing DPX-based therapeutic cancer vaccine(s), with a focus on DPX-0907, aimed at inducing efficient anti-tumor immunity that may eventually be shown to prolong patient survival.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.000 | 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 teacher head, 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".