Identification of new ETV6 modulators through a high-throughput functional screening
Bibliographic record
Abstract
ETV6 transcriptional activity is critical for proper blood cell development in the bone marrow. Despite the accumulating body of evidence linking ETV6 malfunction to hematological malignancies, its regulatory network remains unclear. To uncover genes that modulate ETV6 repressive transcriptional activity, we performed a specifically designed, unbiased genome-wide shRNA screen in pre-B acute lymphoblastic leukemia cells. Following an extensive validation process, we identified 13 shRNAs inducing overexpression of ETV6 transcriptional target genes. We showed that the silencing of AKIRIN1 , COMMD9 , DYRK4 , JUNB, and SRP72 led to an abrogation of ETV6 repressive activity. We identified critical modulators of the ETV6 function which could participate in cellular transformation through the ETV6 transcriptional network.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".