MétaCan
Menu
Back to cohort
Record W4310106406 · doi:10.1182/blood-2022-168958

The Effects of Dietary Asparagine on Pegaspargase Therapy and Blood and Stool Metabolites. a Pilot Study in Mice

2022· article· en· W4310106406 on OpenAlexaffabout
Zara Forbrigger, Tamara MacDonald, Ketan Kulkarni, Andrew W. Stadnyk

Bibliographic record

VenueBlood · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsIzaak Walton Killam Health CentreDalhousie University
Fundersnot available
KeywordsAsparaginaseMedicinePEG ratioGlutamineInternal medicinePharmacologyGastroenterologyPhysiologyImmunologyLymphoblastic LeukemiaBiologyLeukemiaBiochemistryAmino acid

Abstract

fetched live from OpenAlex

Introduction: Pegaspargase (PEG) is key to the treatment of pediatric Acute Lymphoblastic Leukemia. PEG depletes blood asparagine (Asn), killing leukemic but not healthy cells. Guidelines on optimum dosing of PEG are ambiguous. Dietary and gut Asn can diffuse from the gut into the bloodstream through epithelial cells. We also know that some patients have bacteria in the gut that produce asparaginase. It is unclear whether dietary Asn impacts PEG efficacy. In this study we sought to determine if dietary Asn can impact PEG-mediated plasma Asn depletion in a pre-clinical model. Methods: Pre-diet blood and stool samples from 10 healthy, non-tumor-bearing C57BL/6 mice were collected. The mice were then divided into 2 cages and given an Asn rich (4% Asn, cage A) or depleted (0%, cage B) diet. Blood and stool were sampled again 35 and 72 days after commencing the diet. The mice were then injected with 200 IU/kg PEG intraperitoneally. 5-days post-PEG blood and stool samples were collected. Blood PEG activity was immediately quenched following collection using a solution of 20% formic acid to ensure that Asn was not catabolized post collection. Mouse A2 unfortunately received roughly half the PEG in comparison to the other mice and was excluded from the final data summaries. Over 200 blood and stool metabolites were analyzed using LC-MS/MS at each timepoint. ANCOVA was used to test for between-diet significance. MetaboAnalyst 5.0 was used to identify pathways that were different between diets. A p value of ≤0.05 was considered significant. Results: Blood Asn levels were similar between the 2 diets at all time points. Blood and stool metabolomic PCA plots each showed two distinct clusters, with the day 0 samples clustering together and all other sample timepoints in a second cluster. There were some outliers present in the blood PCA plot with mice of both diets on day 77 and one mouse on high Asn on day 35 positioned outside of the clusters. In the stool plot, 3 mice on the 0% diet on day 77 did not cluster with other samples, as well as 1 mouse on the 4% diet, on day 77 (Figure 1). Blood Asn levels were depleted below the level of detection in all the 5-day post PEG samples, the last timepoint of the experiment. There were 5 pathways in pre-diet, 10 on day 35, 12 on day 72, and 4 on day 77 that were significantly different between diets. One pathway of interest that was significantly different on day 72 was aspartate (Asp) metabolism. Asp was significantly higher in the Asn rich group compared to the Asn depleted group. L-acetylaspartylglutamate was higher in the Asn depleted group compared to the Asn rich group (Figure 2). Stool Asn levels were significantly lower in the Asn rich group after 72 days on diet. There were 20 pathways in pre-diet, 5 on day 35, 4 on day 72, and 1 on day 77, that were significantly different between diets. None of the pathways that were different in the blood were also affected at the same time in the stool. Conclusions and Interpretations: Our outcome showing differences late in the diet period demonstrate that diet can have a profound effect on metabolites, not necessarily including Asn. Nevertheless, we provide no evidence that controlling dietary Asn will impact blood Asn levels and PEG efficacy. We found corresponding low stool Asn and high blood Asp in the Asn rich diet after 72 days on the diet. One possible explanation for this is the high Asn diet caused an increase in asparaginase-producing bacteria, which converted the dietary Asn into Asp. The Asp then diffused into the blood from the gut. Further studies examining the genomes of the bacteria present to confirm this theory are underway. Despite changes in metabolites, PEG depleted Asn in mice on both diets. PCA plots revealed that some post-PEG samples did not cluster with the others, indicating that PEG, like diet, could have a profound impact on metabolites. Further studies should examine the microbial and blood changes leading to these outliers. It is also important to take a closer look at the replenishment of Asn post-PEG to see if diet can affect the rate at which blood Asn is restored. The changes we observed and the consequences of these changes, will need to be confirmed in mice with leukemia. Acknowledgement: This research was funded from a grant from the Beatrice Hunter Cancer Research Institute, Dalhousie Medical Research Institute, and ZF was funded by an IWK Health Graduate Studentship. The pegaspargase was kindly provided by Servier Canada Inc. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.021
GPT teacher head0.274
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueBloodSame topicAcute Lymphoblastic Leukemia researchFrench-language works237,207