CSF metabolomic signature during therapy for childhood acute lymphoblastic leukemia predicts subsequent working memory impairment
Bibliographic record
Abstract
BACKGROUND: Although typically curative, treatment for pediatric acute lymphoblastic leukemia (ALL) is associated with neurotoxicity and leads to chemotherapy-related cognitive impairment (CRCI) in 40–70% of survivors. Cerebrospinal fluid (CSF), which is routinely collected during intrathecal chemotherapy, offers a direct window into brain metabolism. This study characterizes longitudinal metabolic changes in the CSF of pediatric patients undergoing chemotherapy for ALL. METHODS: CSF samples from 45 pediatric patients enrolled on the multi-institutional Dana-Farber Cancer Institute (DFCI) ALL Consortium Protocol 16–001 were collected at five standardized timepoints over the first 20 weeks of treatment and analyzed using untargeted metabolomics. Cognitive outcomes were assessed post-treatment using age-appropriate Wechsler Intelligence scales, with the Working Memory Index (WMI) serving as the primary cognitive measure. Patients with WMI scores at least one standard deviation above (n = 21) or below (n = 24) the mean were selected for metabolomic comparison. This study constitutes an exploratory aim of the 16–001 clinical trial. RESULTS: Our analysis revealed a profound reorganization of the CSF metabolome during the first 18 days of treatment, spanning the induction phase of chemotherapy and early leukemia remission. This shift was characterized by alterations in amino acid, phospholipid, and one-carbon metabolism. Moreover, we identified a lipid-rich metabolomic signature predictive of low post-treatment WMI, implicating metabolic dysregulation in CRCI susceptibility. CONCLUSIONS: These findings highlight the dynamic impact of chemotherapy on the CSF metabolome and support its utility as a matrix for monitoring neurotoxicity during pediatric ALL therapy. CSF metabolomics may enable the early identification of patients at risk for CRCI through predictive biomarkers and guide future neuroprotective interventions. Trial registration: Dana-Farber Cancer Institute ALL Consortium Protocol 16–001, clinicaltrials.gov ID NCT03020030; study start date 03/03/2017.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".