PD-1/CTLA-4 Blockade Leads to Expansion of CD8+PD-1int TILs and Results in Tumor Remission in Experimental Liver Cancer
Bibliographic record
Abstract
Background: Checkpoint inhibitors act on exhausted CD8+ T cells and restore their effector function in chronic infections and cancer. The underlying mechanisms of action appear to differ between different types of cancer and are not yet fully understood. Methods: Here, we established a new orthotopic HCC model to study the effects of checkpoint blockade on exhausted CD8+ tumor-infiltrating lymphocytes (TILs). The tumors expressed endogenous levels of HA, which allowed the study of tumor-specific T cells. Results: The induced tumors developed an immune-resistant TME in which few T cells were found. The few recovered CD8+ TILs were mostly terminally exhausted and expressed high levels of PD-1. PD-1/CTLA-4 blockade resulted in a strong increase in the number of CD8+ TILs expressing intermediate amounts of PD-1, also called progenitor-exhausted CD8+ TILs, while terminally exhausted CD8+ TILs were almost absent in the tumors of treated mice. Although transferred naïve tumor-specific T cells did not expand in the tumors of untreated mice, they expanded strongly after treatment and generated progenitor-exhausted but not terminally exhausted CD8+ TILs. Unexpectedly, progenitor-exhausted CD8+ TILs mediated the antitumor response after treatment with minimal changes in their transcriptional profile. Conclusion: In our model, few doses of checkpoint inhibitors during the priming of transferred CD8+ tumor-specific T cells were sufficient to induce tumor remission. Therefore, PD-1/CTLA-4 blockade has an ameliorative effect on the expansion of recently primed CD8+ T cells while preventing their development into terminally exhausted CD8+ TILs in the TME. This finding could have important implications for future T-cell therapies.
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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) | 0.001 | 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".