Engraftment characterization of risk-stratified AML in NSGS mice
Bibliographic record
Abstract
Acute myeloid leukemia (AML) is the most common acute leukemia in adults. Disease heterogeneity is well documented, and patient stratification determines treatment decisions. Patient-derived xenografts (PDXs) from risk-stratified AML are crucial for studying AML biology and testing novel therapeutics. Despite recent advances in PDX modeling of AML, reproducible engraftment of human AML is primarily limited to high-risk (HR) cases, with inconsistent or very protracted engraftment observed for favorable-risk (FR) and intermediate-risk (IR) patients. We used NSGS mice to characterize the engraftment robustness/kinetics of 28 AML patient samples grouped according to molecular/cytogenetic classification and assessed whether the orthotopic coadministration of patient-matched bone marrow mesenchymal stromal cells (BM MSCs) improves AML engraftment. PDX event-free survival correlated well with the predictable prognosis of risk-stratified AML patients. The majority (85-94%) of the mice were engrafted in bone marrow (BM) independently of the risk group, although HR AML patients showed engraftment levels that were significantly superior to those of FR or IR AML patients. Importantly, the engraftment levels observed in NSGS mice by week 6 remained stable over time. Serial transplantation and long-term culture-initiating cell (LTC-IC) assays revealed long-term engraftment limited to HR AML patients, fitter leukemia-initiating cells (LICs) in HR AML samples, and the presence of AML LICs in the CD34- leukemic fraction, regardless of the risk group. Finally, orthotopic coadministration of patient-matched BM MSCs and AML cells was dispensable for BM engraftment levels but favored peripheralization of engrafted AML cells. This comprehensive characterization of human AML engraftment in NSGS mice offers a valuable platform for in vivo testing of targeted therapies in risk-stratified AML patient samples.
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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 | 0.000 | 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 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".