HPK1 competes with ADAP for SLP‐76 binding and <i>via</i> Rap1 negatively affects T‐cell adhesion
Bibliographic record
Abstract
The hematopoietic progenitor kinase 1 (HPK1) signals into MAPK and NFκB pathways downstream of immunoreceptors, but enigmatically is a negative regulator of leukocytes. Here, we report a novel role for HPK1 in regulating the activation of the adhesion molecule leukocyte function-associated antigen-1 (LFA-1). Upon TCR stimulation, mediated by binding of adhesion and degranulation promoting adaptor protein (ADAP) to SLP-76, a ternary complex composed of ADAP/55-kDa src kinase associated phosphoprotein (SKAP-55) and RIAM translocates to the membrane and causes membrane recruitment of the active small GTPase Ras-related protein 1 (Rap1). Active Rap1, via its binding to RapL (regulator for cell adhesion and polarization enriched in lymphoid tissues), mediates LFA-1 integrin activation. We show here that HPK1, which also binds SLP-76, compete with ADAP for SLP-76 binding. In addition, HPK1 dampens Rap1 activation, resulting in decreased LFA-1 activity. Analysis of HPK1-deficient T cells revealed increased ADAP recruitment to SLP-76 and elevated Rap1 activation in those cells, leading to increased adhesion to ICAM-1 and cell spreading. Altogether, these results describe a novel function for HPK1 in linking TCR signaling to cell adhesion regulation and provide a mechanistic explanation for the negative regulatory role of HPK1 in T-cell biology.
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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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".