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Record W4405054871 · doi:10.1182/blood-2024-207258

Mondoa Promotes Resistance to Asparaginase Treatment in B-ALL By Inducing Asparagine Synthesis

2024· article· en· W4405054871 on OpenAlexaff
Alissia Fernandes Madeira, Christian Brückner, Constantin Segner, Alisa Kolesnikova, Alexandra Sipol, Elmar Wolf, Roland Rad, Poul H. Sorensen, Julia Hauer, Jürgen Ruland, S. Burdach

Bibliographic record

VenueBlood · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant tissue culture and regeneration
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAsparaginaseAsparagineBiologyChemistryCancer researchMedicineBiochemistryLeukemiaGeneticsEnzymeLymphoblastic Leukemia

Abstract

fetched live from OpenAlex

Background: Cancer cells often exhibit rapid proliferation and uncontrolled division, employing adaptations to metabolic stress to maintain homeostasis and survival. MondoA (Myc-associated factor X-like protein X-interacting protein [MLXIP]), a member of the MYC interactome, is a metabolic sensor playing an important role in cancer cell adaption to stress. Our previous work demonstrated that increased MondoA expression correlates with poor outcomes in subgroups of pediatric common acute lymphoblastic leukemia (ALL; B-precursor ALL [B-ALL]) by inducing resistance to metabolic stress (Sipol et al. BLOOD 2022). Methods: We explored the role of MondoA in resistance to L-Asparaginase (ASNase) treatment, a major non-genotoxic therapeutic principle in pediatric B-ALL, which depletes Asparagine (Asn) in the bloodstream. Utilizing CRISPR/Cas9 technology, we generated MondoA knock-out B-ALL NALM6 cell line (MKO) to study the effects on cellular metabolism and resistance mechanisms. We tested the effect of ASNase on cell viability and performed multi-omics analyses to evaluate changes in metabolic pathways and MYC binding sites in both MKO and control cells. Results: Our study demonstrates that MondoA induces resistance to ASNase treatment in B-ALL cell lines. In our experiments, MKO cells exhibited a 92% loss of viability upon ASNase treatment, compared to an 84% loss in control cells (N = 4). Mechanistically, MondoA knock-out resulted in a redistribution of MYC binding to promoter regions, significantly affecting the epigenome, transcriptome, and proteome of the cells. Proteomic analysis revealed reduced expression of electron transport chain (ETC) complexes and key tricarboxylic acid (TCA) cycle enzymes, resulting in lower aspartate (Asp) production, a substrate for Asparagine Synthetase (ASNS). Alpha-ketoglutarate supplementation rescued MKO cells, likely by enhancing Asp production through the TCA cycle; this effect was not observed in control cells. Additionally, we discovered that ASNase resistance partially depends on sufficient glutamine (Gln) levels, another substrate for Asn de novo synthesis. Multi-omics coherence analysis of ASNS-promoter MYC binding, transcriptome, and proteome revealed downregulation of ASNS in MKO cells. These data are supported by our previous transcriptome analysis results of MondoA knock-down in other B-ALL cell lines, Reh and 697, which showed downregulation of ASNS transcripts upon silencing MondoA expression. Conclusion: Our findings suggest a pivotal role of MondoA in ASNase therapy-resistant B-ALL and highlight its potential as a therapeutic target to improve treatment outcomes in pediatric B-ALL by enhancing sensitivity to ASNase asparaginase therapy. Key words: B-ALL, MondoA, L-Asparaginase resistance.

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)0.000
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
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.014
GPT teacher head0.253
Teacher spread0.239 · 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
Published2024
Admission routes1
Has abstractyes

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