Generation of highly activated, antigen-specific tumor-infiltrating CD8 <sup>+</sup> T cells induced by a novel T cell-targeted immunotherapy
Bibliographic record
Abstract
The induction of tumor-targeted, cytotoxic T lymphocytes has been recognized as a key component to successful immunotherapy. DPX-based treatment was previously shown to effectively recruit activated CD8+ T cells to the tumor. Herein, we analyze the unique phenotype of the CD8+ T cells recruited into the tumor in response to DPX-based therapy, and how combination with checkpoint inhibitors impacts T cell response. C3-tumor-bearing mice were treated with cyclophosphamide (CPA) for seven continuous days every other week, followed by DPX treatment along with anti-CTLA-4 and/or anti-PD-1. Efficacy, immunogenicity, and CD8+ T cells tumor infiltration were assessed. The expression of various markers, including checkpoint markers, peptide specificity, and proliferation and activation markers, was determined by flow cytometry. tSNE analysis of the flow data revealed a resident phenotype of CD8+ T cells (PD-1+TIM-3+CTLA-4+) within untreated tumors, whereas DPX/CPA treatment induced recruitment of a novel population of CD8+ T cells (PD-1+TIM-3+CTLA-4−) within tumors. Combination of anti-CTLA-4 (ipilimumab) with DPX/CPA versus DPX/CPA alone significantly increased survival and inhibition of tumor growth, without changing overall systemic immunogenicity. Addition of checkpoint inhibitors did not significantly change the phenotype of the newly recruited cells induced by DPX/CPA. Yet, anti-CTLA-4 treatment in combination with DPX/CPA enhanced a non-antigen specific response within the tumor. Finally, the tumor-recruited CD8+ T cells induced by DPX/CPA were highly activated, antigen-specific, and proliferative, while resident phenotype CD8+ T cells, seemingly initially exhausted, were reactivated with combination treatment. This study supports the potential of combining DPX/CPA with ipilimumab to further enhance survival clinically.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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".