Epigenetic mechanisms underlie the crosstalk between growth factors and a steroid hormone
Bibliographic record
Abstract
Crosstalk between growth factors (GFs) and steroid hormones recurs in embryogenesis and is co-opted in pathology, but underlying mechanisms remain elusive. Our data from mammary cells imply that the crosstalk between the epidermal GF and glucocorticoids (GCs) involves transcription factors like p53 and NF-κB, along with reduced pausing and traveling of RNA polymerase II (RNAPII) at both promoters and bodies of GF-inducible genes. Essentially, GCs inhibit positive feedback loops activated by GFs and stimulate the reciprocal inhibitory loops. As expected, no alterations in DNA methylation accompany the transcriptional events instigated by either stimulus, but forced demethylation of regulatory regions broadened the repertoire of GF-inducible genes. We report that enhancers, like some promoters, are poised for activation by GFs and GCs. In addition, within the cooperative interface of the crosstalk, GFs enhance binding of the GC receptor to DNA and, in synergy with GCs, promote productive RNAPII elongation. Reciprocally, within the antagonistic interface GFs hyper-acetylate chromatin at unmethylated promoters and enhancers of genes involved in motility, but GCs hypoacetylate the corresponding regions. In conclusion, unmethylated genomic regions that encode feedback regulatory modules and differentially recruit RNAPII and acetylases/deacetylases underlie the crosstalk between GFs and a steroid hormone.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".