Proteasomal Inhibition Enhances Glucocorticoid Receptor Transactivation and Alters Its Subnuclear Trafficking
Bibliographic record
Abstract
The ubiquitin-proteasome pathway regulates the turnover of many transcription factors, including steroid hormone receptors such as the estrogen receptor and progesterone receptor. For these receptors, proteasome inhibition interferes with steroid-mediated transcription. We show here that proteasome inhibition with MG132 results in increased accumulation of the glucocorticoid receptor (GR), confirming that it is likewise a substrate for the ubiquitin-proteasome degradative pathway. Using the mouse mammary tumor virus (MMTV) promoter integrated into tissue culture cells, we found that proteasome inhibition synergistically increases GR-mediated transactivation. This increased activation was observed in a number of cell lines and on various MMTV templates, either as transiently transfected reporters or stably integrated into chromatin. These observations suggest that the increase in GR-mediated transcription due to proteasome inhibition may occur downstream of the initial chromatin remodeling step. In support of this concept, the increase in transcription did not correlate with an increase in chromatin remodeling, as measured by restriction enzyme hypersensitivity, or transcription factor loading, as exemplified by nuclear factor 1. To investigate the relationship between GR turnover, transcription, and subnuclear trafficking, we examined the effect of proteasome inhibition on the mobility of the GR within the nucleus and association of the GR with the nuclear matrix. Blocking GR turnover reduced the mobility of the GR within the nucleus, and this correlated with increased association of the receptor with the nuclear matrix. As a result of proteasome inhibition, GR mobility within the nucleus was reduced while its association with the nuclear matrix was increased. Thus, while altered nuclear mobility of steroid receptors may be a common feature of proteasome inhibition, GR is unique in its enhanced transactivation activity that results when proteasome function is compromised. Proteasomes may therefore impact steroid receptor action at multiple levels and exert distinct effects on individual receptor types.
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 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 | 0.001 |
| 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".