T505A variant of ETV5 promotes proliferation of precursor B cells in a mouse model of acute lymphoblastic leukemia
Bibliographic record
Abstract
Abstract Precursor B cell acute lymphoblastic leukemia (pre-B-ALL) arises as a result of precursor B cells acquiring driver mutations that lead to arrested differentiation and increased proliferation. Identification of driver mutations and understanding their biological function is critical to understanding pre-B-ALL development and advancing disease treatment. Using a mouse model of pre-B-ALL driven by deletion of genes encoding the related E26-transformation-specific (ETS) transcription factors PU.1 and Spi-B, we performed whole exome sequencing to identify secondary driver mutations. We identified recurrent variants in E26 transformation-specific transcription variant 5 (ETV5) resulting in R392P, V444I, and T505A amino acid changes. We found that the R392P and V444I variants altered the ability of ETV5 to bind to DNA using electrophoretic mobility shift assay. R392P and V444I variants did not activate a Dual-Specificity-Phosphatase 6 (DUSP6) reporter. In contrast, T505A ETV5 could interact with DNA and activate the DUSP6 promoter. To determine biological function, we forced expression of wild type, R392P, V444I, or T505A ETV5 in an interleukin-7-dependent pre-B cell line. Proliferation and apoptosis assays showed that T505A ETV5 conferred a proliferative advantage to pre-B cells. RNA sequencing showed that expression of ETV5 variants significantly altered gene expression in cultured cells. Through gene set enrichment analysis, T505A was suggested to downregulate the p53 pathway and the anti-proliferative protein, B cell translocation gene 2 (encoded by Btg2 ). In summary, these data suggest that ETV5 mutations play a role in pre-B-ALL by affecting proliferation and cell survival.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".