Immunohistochemical expression of conjugating UGT1A‐derived isoforms in normal and tumoral drug‐metabolizing tissues in humans
Bibliographic record
Abstract
Glucuronidation by UDP-glucuronyltransferase (UGT) enzymes is the prevailing conjugative pathway for the metabolism of both xenobiotics and endogenous compounds. Alterations in this pathway, such as those generated by common genetic polymorphisms, have been shown to significantly impact on the health of individuals, influencing cancer susceptibility, responsiveness to drugs and drug-induced toxicity. Alternative usage of terminal exons leads to UGT1A-derived splice variants, namely the classical and enzymatically active isoforms 1 (i1) and the novel enzymatically inactive isoforms 2 (i2). In vitro functional data from heterologous expression and RNA interference experiments indicate that these i2 isoforms act as negative modulators of glucuronidation, likely by forming inactive complexes with active isoform 1. We used specific antibodies against either active i1 or inactive i2 proteins to examine their distribution in major drug-metabolizing tissues. Data revealed that UGT1A_i1 and inactive UGT1A_i2 are co-produced in the same tissue structures, including liver, kidney, stomach, intestine and colon. Examination of the cellular distribution and semi-quantitative level of expression of UGT1As revealed heterogeneous expression of i1 and i2 proteins, with increased expression of i2 in liver tumours and decreased levels of i1 and i2 in colon cancer specimens, compared to normal tissues. These differences in expression may be relevant to human colon and liver cancer tumorigenesis. Our data clearly demonstrate the similar immunolocalization of active and inactive UGT1A isoforms in most UGT1A-expressing cell types of major tissues involved in drug metabolism. These expression patterns are consistent with a dominant-negative function for the i2 encoded by the UGT1A gene.
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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 | 0.001 | 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) | 0.002 | 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".