Amino Acid Stress Response Genes Contribute to a 25‐Fold Increased Risk of L‐Asparaginase–Induced Hypersensitivity
Bibliographic record
Abstract
ABSTRACT Background L‐asparaginase is essential in treating pediatric acute lymphoblastic leukemia (ALL) but is limited by hypersensitivity reactions in up to 70% of patients, leading to severe, dose‐limiting complications and compromised event‐free survival. Procedure This study conducted a genome‐wide association study (GWAS) in a discovery cohort of 221 pediatric cancer patients who experienced l‐asparaginase–induced hypersensitivity reactions (≥CTCAE grade 2) and 705 controls without hypersensitivity despite equivalent exposure. Results were replicated in an independent cohort of 41 cases and 139 controls. Results Significant associations were identified between hypersensitivity and four genes crucial for amino acid stress response: CYP1B1 (rs59569490; odds ratio [OR] = 8.5; 95% confidence interval [CI], 3.9–18.5; p = 1.5 × 10−10), SEC16B (rs115461320; OR = 4.2; 95% CI, 2.5–7.9; p = 1.2 × 10−6), OPLAH (rs11993268; OR = 4.8; 95% CI, 2.4–9.9; p = 2.0 × 10−6), and SORCS2 (rs11940340; OR = 6.7; 95% CI, 2.8–15.7; p = 5.7 × 10−7). Variants in SEC16B, OPLAH, and SORCS2 remained significant in the analysis of the replication cohort (p < 0.05). Patients who carried risk alleles in two or more of these genes experienced an 86.4% increased incidence of hypersensitivity reactions in the discovery cohort (OR = 25.2; 95% CI, 7.4–86.2; p = 1.0 × 10−10), which was replicated in the independent cohort with a 100% incidence in carriers (p = 0.04). Conclusions The cumulative incidence of these large effect variants highlights their significance for the identification of patients at high risk of l‐asparaginase–induced hypersensitivity. Successfully identifying patients at increased risk of hypersensitivity reactions can inform personalized treatment strategies and limit these harmful dose‐limiting reactions in pediatric ALL.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".