Regulation of UGT1A1 and HNF1 transcription factor gene expression by DNA methylation in colon cancer cells
Bibliographic record
Abstract
BACKGROUND: UDP-glucuronosyltransferase 1A1 (UGT1A1) is a pivotal enzyme involved in metabolism of SN-38, the active metabolite of irinotecan commonly used to treat metastatic colorectal cancer. We previously demonstrated aberrant methylation of specific CpG dinucleotides in UGT1A1-negative cells, and revealed that methylation state of the UGT1A1 5'-flanking sequence is negatively correlated with gene transcription. Interestingly, one of these CpG dinucleotides (CpG -4) is found close to a HNF1 response element (HRE), known to be involved in activation of UGT1A1 gene expression, and within an upstream stimulating factor (USF) binding site. RESULTS: Gel retardation assays revealed that methylation of CpG-4 directly affect the interaction of USF1/2 with its cognate sequence without altering the binding for HNF1-alpha. Luciferase assays sustained a role for USF1/2 and HNF1-alpha in UGT1A1 regulation in colon cancer cells. Based on the differential expression profiles of HNF1A gene in colon cell lines, we also assessed whether methylation affects its expression. In agreement with the presence of CpG islands in the HNF1A promoter, treatments of UGT1A1-negative HCT116 colon cancer cells with a DNA methyltransferase inhibitor restore HNF1A gene expression, as observed for UGT1A1. CONCLUSIONS: This study reveals that basal UGT1A1 expression in colon cells is positively regulated by HNF1-alpha and USF, and negatively regulated by DNA methylation. Besides, DNA methylation of HNF1A could also play an important role in regulating additional cellular drug metabolism and transporter pathways. This process may contribute to determine local inactivation of drugs such as the anticancer agent SN-38 by glucuronidation and define tumoral response.
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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".