Fusion of Early B Cell Factor 1 with Platelet-Derived Growth Factor Receptor Beta in B-ALL disrupts functions necessary for normal B lymphopoiesis
Bibliographic record
Abstract
Abstract Human B cell Acute Lymphoblastic Leukemia (B-ALL) cells often lack functional genes encoding Early B cell Factor 1 (EBF1). EBF1 is essential for B lineage specification, where it regulates >500 genes necessary for normal B cell development. Here, we describe molecular mechanisms that contribute to EBF1-associated B-ALL. Intra-chromosomal deletions result in fusion of the nearly complete EBF1 gene with the 3′ half of the Platelet-Derived Growth Factor Receptor Beta gene (EBF1:PDGFRB) in a subset of high risk pediatric B-ALL. The fusion protein, EBF1:PDGFRβ, unifies loss of EBF1 function with a proliferative advantage due to unregulated Receptor Tyrosine Kinase (RTK) activity of PDGFRβ. Our laboratory has utilized biochemical, cell-based, and fluorescence microscopy approaches to study DNA binding, transcriptional activation and repression, oligomerization, and localization of EBF1:PDGFRβ in B cells. EBF1:PDGFRβ transforms B cell progenitors by eliminating their dependence on IL-7. Although the fusion protein includes nearly intact EBF1 and its nuclear localization signal, EBF1:PDGFRβ localizes predominately in the cytosol. Localization of EBF1:PDGFRβ is dependent upon the transmembrane (TM) domain of PDGFRβ; however, rather than docking EBF1:PDGFRβ in the plasma membrane, the TM functions as a nuclear export signal. Treatment with the tyrosine kinase inhibitor (TKI) imatinib reduces RTK activity and partially restores transactivation of EBF1 target genes by EBF1:PDGFRβ. This suggests a potentially undesirable effect of TKI chemotherapy, which could allow evasion of leukemic cells and disease relapse. Our data suggests that the TM domain of PDGFRβ could serve as a therapeutic target to supplement TKI chemotherapy.
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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 | 0.001 |
| 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".