A novel SLP-76 signaling pathway T-cells that controls cancer immunotherapy
Bibliographic record
Abstract
Abstract The receptors and signaling pathways that regulate T-cell activation are central in the control of immune responses against tumors. In addition to proximal kinases such as p56lck and downstream immune cell adaptors, we have identified a new signaling pathway in T-cells that involves the direct regulation of the nuclear pore complex (NPC) by the binding of immune adaptor SLP-76 to SUMO-RanGAP1 of the NPC (Mol Cell 2015 59(5):840–9). This interaction represents a second checkpoint for NFATc1 nuclear entry and accounts for some 40–50% of transcription factor entry into the nucleus. RanGAP1 binds to a motif in SLP-76 involving the lysine at residue 56 where its mutation ablates complex formation. In this new study, we report the generation of K56E SLP-76 knock-in (KI) mice which are markedly impaired in the control of tumor growth. This loss of control was accompanied by a marked reduction in the presence CD8+ effector TILs and in the production of interferon-g1 and CD8 cytolytic effector molecules, perforin and granzyme B (GZMB). Further, K56E T-cells showed an impairment in metabolism. Seahorse analysis showed a >70% decrease in glycolysis in response to TCR ligation due to this single mutation in a single adaptor protein. Moreover, K56E T-cells showed a decrease in the expression of Glut1 and in c-Myc translocation into the nucleus of T-cells. By contrast, the expression of other mediators such as PPARα and CPT-1A in fatty acid oxidation were unaffected. Our findings identify a novel SLP-76-RanGAP1 signaling pathway in T-cells that controls transcription factor entry into the nucleus and which modulates immunity against tumors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".