Novel strategy for rapid functional in vivo validation of oncogenic drivers in haematological malignancies
Bibliographic record
Abstract
Abstract In cancer research, it remains challenging to functionally validate putative novel oncogenic drivers and to establish relevant preclinical models for evaluation of novel therapeutic strategies. Here, we describe an optimized and efficient pipeline for the generation of novel conditional overexpression mouse models in which putative oncogenes, along with an eGFP/Luciferase dual reporter, are expressed from the endogenous ROSA26 (R26) promoter. The efficiency of this approach was demonstrated by the generation and validation of novel R26 knock-in (KI) mice that allow conditional overexpression of Jarid2 , Runx2 , MN1 and a dominant negative allele of ETV6. As proof of concept, we confirm that MN1 overexpression in the hematopoietic lineage is sufficient to drive myeloid leukemia. In addition, we show that T-cell specific activation of MN1 in combination with loss of Pten increases tumour penetrance and stimulates the formation of Lyl1 + murine T-cell lymphoblastic leukemias or lymphomas (T-ALL/T-LBL). Finally, we demonstrate that these luciferase-positive murine AML and T-ALL/T-LBL cells are transplantable into immunocompromised mice allowing preclinical evaluation of novel anti-leukemic drugs in vivo .
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 | 0.000 |
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".