Rasal1 regulates stemness and exhaustion of CD8 T-cells for more effective anti-PD-1 tumor immunity 3588
Bibliographic record
Abstract
Abstract Description Rasal1, a GTPase-activating protein (GAP) that interacts with the T-cell receptor (TCR), inhibits the activation of ZAP-70 and the p21ras-ERK signaling pathways in T cells. Despite the success of anti-PD-1 immune checkpoint blockade (ICB), the underlying intracellular pathways that influence its effectiveness are unclear. In this study, we reveal that Rasal1 is a novel intracellular checkpoint regulator, influencing the stemness and exhaustion of tumor-infiltrating lymphocytes (TILs) in tumor immunity. Mice with a loss-of-function Rasal1c-mut showed altered cellularity of the thymus and peripheral CD4+ and CD8+ T cells. Concomitantly, these mice exhibited a greater ability to control tumor growth, which correlated with an increased presence of CD8+effector-memory TILs. Further, investigations revealed that Rasal1c-mut T cells displayed hyperactivated ZAP-70 and ERK1/2 signaling pathways, coupled with an increase in the mitochondrial-based oxidative phosphorylation pathway in T-cells. Further, surprisingly, the combination of anti-PD-1 blockade with Rasal1c-mut exhibited a synergistic effect in controlling tumor growth. This effect was associated with a reduction in T-cell exhaustion and the emergence of self-replicating TCF1+ stem-like CD8+ TILs. Collectively, our study emphasizes the critical role of Rasal1 in cooperating with anti-PD-1 blockade to limit T-cell exhaustion and generate stem-like TILs, thereby promoting more effective anti-tumor immunity. Funding Sources Canadian Institutes of Health Research Foundation grant (159912) Topic Categories Tumor Immunology: Cellular Responses and Tumor Microevironment (TIME)
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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) | 0.000 | 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) | 0.001 | 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".