PU.1 eviction at lymphocyte-specific chromatin domains mediates glucocorticoid response in acute lymphoblastic leukemia
Bibliographic record
Abstract
The epigenetic landscape plays a critical role in cancer progression, yet its therapeutic potential remains underexplored. Glucocorticoids are essential components of treatments for lymphoid cancers, but resistance, driven in part by epigenetic changes at glucocorticoid-response elements, poses a major challenge to effective therapies. Here we show that glucocorticoid treatment induces distinct patterns of chromosomal organization in glucocorticoid-sensitive and resistant acute lymphoblastic leukemia xenograft models. These glucocorticoid-response elements are primed by the pioneer transcription factor PU.1, which interacts with the glucocorticoid receptor. Eviction of PU.1 promotes receptor binding, increasing the expression of genes involved in apoptosis and facilitating a stronger therapeutic response. Treatment with a PU.1 inhibitor enhances glucocorticoid sensitivity, demonstrating the clinical potential of targeting this pathway. This study uncovers a mechanism involving PU.1 and the glucocorticoid receptor, linking transcription factor activity with drug response, and suggesting potential therapeutic strategies for overcoming resistance. Glucocorticoid resistance is partly due to epigenetic alterations, but the regulatory mechanisms driving these remain poorly understood. Here, a link between the activity of a lineage-specific transcription factor PU.1 and epigenetic modulators mediating the response to glucocorticoids is described in acute lymphoblastic leukemia.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".