Regulation of the adaptor molecule LAT2, an <i>in vivo</i> target gene of AML1/ETO (<i>RUNX1/RUNX1T1</i>), during myeloid differentiation
Bibliographic record
Abstract
The leukaemia-specific fusion oncoprotein RUNX1/RUNX1T1 (AML1/ETO), resulting from the chromosomal translocation (8;21) in acute myeloid leukaemia (AML), imposes a striking genotype-phenotype relationship upon this distinct subtype of AML, which is mediated by multiple, co-ordinate downstream effects induced by this chimeric transcription factor. We previously identified the LAT2 gene, encoding the adaptor molecule LAT2 (NTAL, LAB), which is phosphorylated by KIT and has a role in mast cell and B-cell activation, as a target of the repressor activity of RUNX1/RUNX1T1. These results were confirmed and extended by demonstrating downregulation of the LAT2 protein in response to conditional RUNX1/RUNX1T1 expression, and its absence in primary AML with the t(8;21). In contrast, in a cohort of 43 AML patients, higher levels of LAT2 were associated with myelomonocytic features. Differentiation of HL-60 and NB4 cells towards granulocytes by all trans-retinoic acid (ATRA) resulted in downregulation of LAT2; conversely, it was upregulated during phorbol ester-induced monocytic differentiation of HL-60 cells. Forced expression of LAT2 in Kasumi-1 cells resulted in a striking block of ATRA- and phorbol ester-induced differentiation, implicating disturbances of the graded expression of this adaptor molecule in the maturation block of myeloid leukaemia cells.
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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 | 0.001 |
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".