Emerging roles for UDP-glucuronosyltransferases in drug resistance and cancer progression
Bibliographic record
Abstract
The best-known role of UDP-glucuronosyltransferase enzymes (UGTs) in cancer is the metabolic inactivation of drug therapies. By conjugating glucuronic acid to lipophilic drugs, UGTs impair the biological activity and enhance the water solubility of these agents, driving their elimination. Multiple clinical observations support an expanding role for UGTs as modulators of the drug response and in mediating drug resistance in numerous cancer types. However, accumulating evidence also suggests an influence of the UGT pathway on cancer progression. Dysregulation of the expression and activity of UGTs has been associated with the progression of several cancers, arguing for UGTs as possible mediators of oncogenic pathways and/or disease accelerators in a drug-naive context. The consequences of altered UGT activity on tumour biology are incompletely understood. They might be associated with perturbed levels of bioactive endogenous metabolites such as steroids and bioactive lipids that are inactivated by UGTs or through non-enzymatic mechanisms, thereby eliciting oncogenic signalling cascades. This review highlights the evidence supporting dual roles for the UGT pathway, affecting cancer progression and drug resistance. Pharmacogenomic testing of UGT profiles in patients and the development of therapeutic options that impair UGT actions could provide useful prognostic and predictive biomarkers and enhance the efficacy of anti-cancer drugs.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.000 | 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".