Zinc Finger Nuclease–Mediated Knockout of AHR or ARNT in Human Breast Cancer Cells Abolishes Basal and Ligand-Dependent Regulation of CYP1B1 and Differentially Affects Estrogen Receptor α Transactivation
Bibliographic record
Abstract
In this study, we used zinc finger nuclease-mediated knockout of the aryl hydrocarbon receptor (AHR) or AHR nuclear translocator (ARNT) in MCF7 and AHR knockout in MDA-MB-231 human breast cancer cells to investigate cross talk among AHR, ARNT, and estrogen receptor α (ERα). Knockout of AHR or ARNT prevented the 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)-dependent induction of all AHR target genes examined. Knockout of AHR or ARNT also significantly reduced basal cytochrome P4501B1 (CYP1B1) expression levels, which were restored with overexpression of either protein but not with a DNA binding-deficient AHR mutant. Basal and TCDD-, 17β-estradiol (E2)-, or TCDD + E2-dependent recruitment of AHR, ARNT, ERα, NCoA3, and RNA polymerase II to CYP1B1 as well as CYP1B1 mRNA levels were abolished in MCF7-AHR((ko)) and MDA-MB-231 AHR(ko) cells. However, reduced but significant E2-dependent recruitment of ERα, NCoA3, and RNA polymerase II to CYP1B1 and weak increases in CYP1B1 mRNA levels were observed in MCF7 ARNT((ko)) cells. Interestingly, E2-dependent increases in trefoil factor 1, but not growth regulation by estrogen in breast cancer 1 (GREB1) mRNA levels, were dependent on ARNT expression. Moreover, the TCDD-dependent increases in the proteolytic degradation of ERα were prevented by the loss of AHR or ARNT. Our data show that AHR and ARNT play critical roles in the basal, TCDD, and E2-induced regulation of CYP1B1 but also reveal distinct roles for both proteins in ERα transactivation.
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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 | 0.000 | 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) | 0.000 | 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".