A human-like glutaminase-free asparaginase is highly efficacious in ASNSlow leukemia and solid cancer mouse xenograft models
Bibliographic record
Abstract
L-asparaginase (L-ASNase) is crucial in treating pediatric acute lymphoblastic leukemia (ALL), but its use is hampered by side effects from the immunogenicity and L-glutaminase (L-GLNase) co-activity of FDA-approved bacterial L-ASNases, often leading to treatment discontinuation and poor outcomes. The toxicity of these L-ASNases makes them especially challenging to use in adult cancer patients. To overcome these issues, we developed EBD-200, a humanized guinea pig L-ASNase with low Km and no L-GLNase activity, eliminating glutamine-related toxicity. EBD-200 showed comparable anti-cancer effects to PEGylated L-ASNase in ASNS low ALL, melanoma and liver cancer models, with improved tolerability. Its potent anti-cancer efficacy and enhanced safety profile suggest that EBD-200 could benefit ALL patients and broaden treatment options for ASNS low solid cancers. • Similar durable in vivo anti-leukemic effect is seen with EBD-200 and PEG-ASNase. • Lower toxicity of EBD-200 versus PEG-ASNase correlates with lack of GLNase activity. • EBD-200 effectively treats ASNS low solid cancers with hypermethylated ASNS promoter.
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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 | 0.001 | 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 | 0.001 |
| 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".