UGT2B17 modifies drug response in chronic lymphocytic leukaemia
Bibliographic record
Abstract
BACKGROUND: High UGT2B17 is associated with poor prognosis in untreated chronic lymphocytic leukaemia (CLL) patients and its expression is induced in non-responders to fludarabine-containing regimens. We examined whether UGT2B17, the predominant lymphoid glucuronosyltransferase, affects leukaemic drug response and is involved in the metabolic inactivation of anti-leukaemic agents. METHODS: Functional enzymatic assays and patients' plasma samples were analysed by mass-spectrometry to evaluate drug inactivation by UGT2B17. Cytotoxicity assays and RNA sequencing were used to assess drug response and transcriptome changes associated with high UGT2B17 levels. RESULTS: High UGT2B17 in B-cell models led to reduced sensitivity to fludarabine, ibrutinib and idelalisib. UGT2B17 expression in leukaemic cells involved a non-canonical promoter and was induced by short-term treatment with these anti-leukaemics. Glucuronides of both fludarabine and ibrutinib were detected in CLL patients on respective treatment, however UGT2B17 conjugated fludarabine but not ibrutinib. AMP-activated protein kinase emerges as a pathway associated with high UGT2B17 in fludarabine-treated patients and drug-treated cell models. The expression changes linked to UGT2B17 exposed nuclear factor kappa B as a key regulatory hub. CONCLUSIONS: Data imply that UGT2B17 represents a mechanism altering drug response in CLL through direct inactivation but would also involve additional mechanisms for drugs not inactivated by UGT2B17.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".