Overexpression of uridine diphospho glucuronosyltransferase 2B17 in high-risk chronic lymphocytic leukemia
Bibliographic record
Abstract
Uridine diphospho glucuronosyltransferase 2B17 (UGT2B17) glucuronidates androgens and xenobiotics including certain drugs. The UGT2B17 gene shows a remarkable copy number variation (CNV), which predisposes for solid tumors and influences drug response. Here, we identify a yet undescribed UGT2B17 mRNA overexpression in poor-risk chronic lymphocytic leukemia (CLL). In total, 320 CLL patients and 449 healthy donors were analyzed. High (above median) UGT2B17 expression was associated with established CLL poor prognostic factors and resulted in shorter treatment-free and overall survival (hazard ratio ([death] 2.18; 95% CI 1.18-4.01; P = .013). The prognostic impact of mRNA expression was more significant than that of UGT2B17 CNV. UGT2B17 mRNA levels in primary CLL samples directly correlated with functional glucuronidation activity toward androgens and the anticancer drug vorinostat (R > 0.9, P < .001). After treatment with fludarabine containing regimens UGT2B17 was up-regulated particularly in poor responders (P = .030). We observed an exclusive involvement of the 2B17 isoform within the UGT protein family. Gene expression profiling of a stable UGT2B17 knockdown in the CLL cell line MEC-1 demonstrated a significant involvement in key cellular processes. These findings establish a relevant role of UGT2B17 in CLL with functional consequences and potential therapeutic implications.
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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 | 0.000 |
| 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".