Immunotherapy-induced CD8+ T Cells Instigate Immune Suppression in the Tumor
Bibliographic record
Abstract
Despite clear evidence of immunogenicity, cancer vaccines only provide a modest clinical benefit. To evaluate the mechanisms that limit tumor regression following vaccination, we have investigated the weak efficacy of a highly immunogenic experimental vaccine using a murine melanoma model. We discovered that the tumor adapts rapidly to the immune attack instigated by tumor-specific CD8+ T cells in the first few days following vaccination, resulting in the upregulation of a complex set of biological networks, including multiple immunosuppressive processes. This rapid adaptation acts to prevent sustained local immune attack, despite continued infiltration by increasing numbers of tumor-specific T cells. Combining vaccination with adoptive transfer of tumor-specific T cells produced complete regression of the treated tumors but did not prevent the adaptive immunosuppression. In fact, the adaptive immunosuppressive pathways were more highly induced in regressing tumors, commensurate with the enhanced level of immune attack. Examination of tumor infiltrating T-cell functionality revealed that the adaptive immunosuppression leads to a progressive loss in T-cell function, even in tumors that are regressing. These novel observations that T cells produced by therapeutic intervention can instigate a rapid adaptive immunosuppressive response within the tumor have important implications for clinical implementation of immunotherapies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".