Enhanced immunotherapeutic profile of oncolytic virus-based cancer vaccination using cyclophosphamide preconditioning
Bibliographic record
Abstract
T-cell responses in a murine model of disseminated pulmonary melanoma. Significant increases in the number and quality of circulating effector T-cells were documented when low-dose cyclophosphamide (CTX) was administered pre-vaccination to tumor-bearing but not tumor-free hosts. Interestingly, tumor-bearing mice receiving CTX and co-primed with a melanoma differentiation antigen together with an irrelevant control antigen exhibited significantly enhanced immunity against the tumor, but not the control antigen, in secondary lymphoid organs. This result highlighted an increased cancer-specific reactivity of vaccine-induced T-cell responses following CTX preconditioning. Additionally, an acute reduction of the frequency of peripheral regulatory T-cells (Tregs) was noticeable, particularly in the proliferating, presumably tumour-reactive, subset. Enhanced infiltration of lungs with multifunctional T-cells resulted in overt reduction in metastatic burden in mice pretreated with CTX. Despite doubling the median survival in comparison to untreated controls, most vaccinated mice ultimately succumbed to cancer progression. However, preconditioning of the virus-based vaccination with CTX resulted in a remarkable improvement of the therapeutic activity leading to complete remission in the majority of the animals. Collectively, these data reveal how CTX can potentiate specific cellular immunity in an antigen-restricted manner that is only observed in vaccinated tumor-bearing hosts while depleting replicating Tregs. A single low dose of CTX enhances antitumor immunity and the efficacy of this potent prime:boost platform by modulating the kinetics of the vaccine-specific responses. Clinical assessment of CTX combined with next-generation cancer vaccines is indicated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".