The PKN1- TRAF1 signaling axis as a potential new target for chronic lymphocytic leukemia
Bibliographic record
Abstract
TRAF1 is a pro-survival adaptor molecule in TNFR superfamily (TNFRSF) signaling. TRAF1 is overexpressed in many B cell cancers including refractory chronic lymphocytic leukemia (CLL). Little has been done to assess the role of TRAF1 in human cancer. Here we show that the protein kinase C related kinase Protein Kinase N1 (PKN1) is required to protect TRAF1 from cIAP-mediated degradation during constitutive CD40 signaling in lymphoma. We show that the active phospho-Thr774 form of PKN1 is constitutively expressed in CLL but minimally detected in unstimulated healthy donor B cells. Through a screen of 700 kinase inhibitors, we identified two inhibitors, OTSSP167, and XL-228, that inhibited PKN1 in the nanomolar range and induced dose-dependent loss of TRAF1 in RAJI cells. OTSSP167 or XL-228 treatment of primary patient CLL samples led to a reduction in TRAF1, pNF-κB p65, pS6, pERK, Mcl-1 and Bcl-2 proteins, and induction of activated caspase-3. OTSSP167 synergized with venetoclax in inducing CLL death, correlating with loss of TRAF1, Mcl-1, and Bcl-2. Although correlative, these findings suggest the PKN1-TRAF1 signaling axis as a potential new target for CLL. These findings also suggest the use of the orally available inhibitor OTSSP167 in combination treatment with venetoclax for TRAF1 overexpressing CLL.
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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".