A cell-type-specific transcriptional network required for estrogen regulation of cyclin D1 and cell cycle progression in breast cancer
Bibliographic record
Abstract
Estrogen stimulates the proliferation of the most common type of human breast cancer that expresses estrogen receptor alpha (ERalpha) through the activation of the cyclin D1 (CCND1) oncogene. However, our knowledge of ERalpha transcriptional mechanisms remains limited. Hence, it is still elusive why ERalpha ectopically expressed in ER-negative breast cancer cells (BCC) is functional on ectopic reporter constructs but lacks activity on many endogenous target genes, including CCND1. Here, we show that estradiol (E2) stimulation of CCND1 expression in BCC depends on a novel cell-type-specific enhancer downstream from the CCND1 coding region, which is the primary ERalpha recruitment site in estrogen-responsive cells. The pioneer factor FoxA1 is specifically required for the active chromatin state of this enhancer and as such is crucial for both CCND1 expression and subsequent cell cycle progression. Interestingly, even in BCC, CCND1 levels and proliferation are tightly controlled by E2 through the establishment of a negative feedforward loop involving the induction of NFIC, a putative tumor suppressor capable of directly repressing CCND1 transcription. Taken together, our results reveal an estrogen-regulated combinatorial network including cell-specific cis- and trans-regulators of CCND1 expression where ERalpha collaborates with other transcription factors associated with the ER-positive breast cancer phenotype, including FoxA1 and NFIC.
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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".