A Novel Human Cytochrome P450, CYP26C1, Involved in Metabolism of 9-cis and All-trans Isomers of Retinoic Acid
Bibliographic record
Abstract
Retinoids are potent regulators of cell proliferation, cell differentiation, and morphogenesis and are important therapeutic agents in oncology and dermatology. The gene regulatory activity of endogenous retinoids is effected primarily by retinoic acid isomers (all-trans and 9-cis) that are synthesized from retinaldehyde precursors in a broad range of tissues and act as ligands for nuclear retinoic acid receptors. The catabolism of all-trans-retinoic acid (atRA) is an important mechanism of controlling RA levels in cell and tissues. We have previously identified two cytochrome P450s, P450RAI-1 and P450RAI-2 (herein named CYP26A1 and CYP26B1), which were shown to be responsible for catabolism of atRA both in the embryo and the adult. In this report, we describe the identification, molecular cloning, and substrate characterization of a third member of the CYP26 family, named CYP26C1. Transiently transfected cells expressing CYP26C1 convert atRA to polar water-soluble metabolites similar to those generated by CYP26A1 and -B1. Competition studies with all-trans, 13-cis, and 9-cis isomers of retinoic acid demonstrated that atRA was the preferred substrate for CYP26C1. Although CYP26C1 shares extensive sequence similarity with CYP26A1 and CYP26B1, its catalytic activity appears distinct from those of other CYP26 family members. Specifically, CYP26C1 can also recognize and metabolize 9-cis-RA and is much less sensitive than the other CYP26 family members to the inhibitory effects of ketoconazole. CYP26C1 is not widely expressed in the adult but is inducible by RA in HPK1a, transformed human keratinocyte cell lines. This third CYP26 member may play a specific role in catabolizing both all-trans and 9-cis isomers of RA.
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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 | 0.001 |
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".