Focused chemical genomics using zebrafish xenotransplantation as a pre-clinical therapeutic platform for T-cell acute lymphoblastic leukemia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Cancer therapeutics is evolving to precision medicine, with the goal of matching targeted compounds with molecular aberrations underlying a patient's cancer. While murine models offer a pre-clinical tool, associated costs and time are not compatible with actionable patient-directed interventions. Using the paradigm of T-cell acute lymphoblastic leukemia, a high-risk disease with defined molecular underpinnings, we developed a zebrafish human cancer xenotransplantation model to inform therapeutic decisions. Using a focused chemical genomic approach, we demonstrate that xenografted cell lines harboring mutations in the NOTCH1 and PI3K/AKT pathways respond concordantly to their targeted therapies, patient-derived T-cell acute lymphoblastic leukemia can be successfully engrafted in zebrafish and specific drug responses can be quantitatively determined. Using this approach, we identified a mutation sensitive to γ-secretase inhibition in a xenograft from a child with T-cell acute lymphoblastic leukemia, confirmed by Sanger sequencing and validated as a gain-of-function NOTCH1 mutation. The zebrafish xenotransplantation platform provides a novel cost-effective means of tailoring leukemia therapy in real time.
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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 | 0.000 | 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) | 0.000 | 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 it