Reduced PRC2 function causes asparaginase resistance in T-ALL by decreasing WNT pathway activity
Bibliographic record
Abstract
ABSTRACT: Loss-of-function mutations and deletions in the core components of the epigenetic polycomb repressive complex 2 (PRC2) are associated with poor initial treatment response in T-cell acute lymphoblastic leukemia (T-ALL), but the mechanisms that underpin resistance to individual therapies are unknown. We leveraged an isogenic T-ALL cellular model and primary patient data to investigate how PRC2 alterations affect signaling pathway activity in leukemia cells, and whether these changes may influence therapy response. The integration of transcriptomic, proteomic, and phosphoproteomic results revealed markedly reduced activity of the WNT-dependent stabilization of proteins (WNT/STOP) pathway in leukemia cells lacking core PRC2 factor EZH2. Importantly, these results closely matched transcriptional readouts from the samples of patients with T-ALL with PRC2 mutations and deletions. We discovered that PRC2 loss significantly reduced sensitivity to key T-ALL treatment asparaginase, and that this was mechanistically linked to increased cellular ubiquitination levels due to WNT/STOP suppression, which bolstered the asparagine reserves of leukemia cells. These results also strongly correlated with transcriptional profiles of asparaginase resistance in an independent cohort of patients with T-ALL. We further found that asparaginase resistance in PRC2-depleted leukemic blasts could be mitigated by pharmaceutical proteasome inhibition, thereby providing a potential avenue to tackle induction treatment failure in these cases.
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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 | 0.000 | 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) | 0.001 | 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 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".