A Non-Canonical Role for the Glycosyltransferase Enzyme UGT2B17 as a Novel Constituent of the B Cell Receptor Signalosome
Bibliographic record
Abstract
In chronic lymphocytic leukemia (CLL), an elevated glycosyltransferase UGT2B17 expression (UGT2B17HI) identifies a subgroup of patients with shorter survival and poor drug response. We uncovered a mechanism, possibly independent of its enzymatic function, characterized by an enhanced expression and signaling of the proximal effectors of the pro-survival B cell receptor (BCR) pathway and elevated Bruton tyrosine kinase (BTK) phosphorylation in B-CLL cells from UGT2B17HI patients. A prominent feature of B-CLL cells is the strong correlation of UGT2B17 expression with the adverse marker ZAP70 encoding a tyrosine kinase that promotes B-CLL cell survival. Their combined high expression levels in the treatment of naïve patients further defined a prognostic group with the highest risk of poor survival. In leukemic cells, UGT2B17 knockout and repression of ZAP70 reduced proliferation, suggesting that the function of UGT2B17 might involve ZAP70. Mechanistically, UGT2B17 interacted with several kinases of the BCR pathway, including ZAP70, SYK, and BTK, revealing a potential therapeutic vulnerability. The dual SYK and JAK/STAT6 inhibitor cerdulatinib most effectively compromised the proliferative advantage conferred by UGT2B17 compared to the selective BTK inhibitor ibrutinib. Findings point to an oncogenic role for UGT2B17 as a novel constituent of BCR signalosome also connected with microenvironmental signaling.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".