Inhibition of Src family kinases enhances retinoic acid–induced gene expression and myeloid differentiation
Bibliographic record
Abstract
Treatment of acute promyelocytic leukemia with retinoic acid (RA) results in differentiation of the leukemic cells and clinical remission. However, the cellular factors that regulate RA-induced myeloid differentiation are largely unknown, and other forms of acute myelogenous leukemia (AML) do not respond to this differentiation therapy. A greater understanding of the molecules that positively or negatively regulate RA-induced differentiation should facilitate the development of more effective differentiation therapies. In this study, we investigated the potential role of Src family kinases (SFK) in the regulation of RA-induced gene expression and myeloid differentiation. We report that inhibition of SFKs markedly enhanced RA-induced differentiation in myeloid cell lines and primary AML cells, as assessed by flow-cytometric analysis of cell surface markers, morphologic analysis, and nitroblue tetrazolium reduction. In addition, inhibition of SFKs enhanced expression from retinoic acid receptor (RAR) target genes encoding CCAAT/enhancer binding protein epsilon (C/EBPepsilon), PU.1, intercellular adhesion molecule-1 (ICAM-1), and cathepsin D. Moreover, a constitutively active Src inhibited RAR-dependent transcription, whereas a kinase-dead Src exerted little effect. These studies provide the first demonstration that SFKs act to negatively regulate RA-induced gene expression and myeloid differentiation and suggest that the combination of SFK inhibition and RA treatment may be therapeutically beneficial in AML.
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 | 0.000 | 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".