GTPase-activating protein Rasal1 associates with ZAP-70 of the TCR and negatively regulates T-cell tumor immunity
Bibliographic record
Abstract
Abstract Immunotherapy involving checkpoint blockades of inhibitory co-receptors is effective in combating cancer. Despite this, the full range of mediators that inhibit T-cell activation and influence anti-tumor immunity is unclear. Here, we identify the GTPase-activating protein (GAP) Rasal1 as a novel TCR-ZAP-70 binding protein that negatively regulates T-cell activation and tumor immunity. Rasal1 inhibits via two pathways, the binding and inhibition of the kinase domain of ZAP-70, and GAP inhibition of the p21ras-ERK pathway. It is expressed in activated CD4 + and CD8 + T-cells, and inhibits CD4 + T-cell responses to antigenic peptides presented by dendritic cells as well as CD4 + T-cell responses to peptide antigens in vivo. Furthermore, siRNA reduction of Rasal1 expression in T-cells shrinks B16 melanoma and EL-4 lymphoma tumors, concurrent with an increase in CD8 + tumor-infiltrating T-cells expressing granzyme B and interferon γ-1. Our findings identify ZAP-70-associated Rasal1 as a new negative regulator of T-cell activation and tumor immunity.
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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 | 0.001 |
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".