Single-cell proteogenomic analysis of clonal evolution in PDX models of AML treated with IDH inhibitors
Bibliographic record
Abstract
1. Single-cell proteogenomic analysis of AML PDX models offers the potential to study clonal evolution in response to different therapies. 2. Co-transplanting multiple primary samples into a single animal can generate PDX models with the desired genetic composition. Clonal heterogeneity in acute myeloid leukemia (AML) can drive drug resistance because different clones may respond variably to treatments. Studying the evolution of these clones under the influence of therapeutic selective pressures is important for designing strategies to overcome drug resistance. Here, we used single-cell proteogenomic analysis to monitor the clonal evolution and differentiation of isocitrate dehydrogenase ( IDH )-mutated AML in patient-derived xenografts (PDXs) treated with IDH inhibitors alone or in combination with other anti-leukemic therapies. Furthermore, we generated mixed PDX models by co-engrafting two or more leukemic samples into the same animal and used single-cell DNA sequencing to deconvolute their clonal composition. Using these models, we tracked clonal evolution under selective pressure from IDH inhibitors and combination therapies, identifying an association between WT1 mutations and ivosidenib (IDH1 inhibitor) monotherapy resistance and antagonism between ivosidenib and enasidenib (IDH2 inhibitor) when tested in IDH1 -mutated cells. Our findings demonstrate how single-cell proteogenomic analysis of PDX models can illuminate drug resistance mechanisms and inform therapeutic strategies.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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".