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Record W4362593963 · doi:10.1158/1538-7445.am2023-ng07

Abstract NG07: Targeting polyamines metabolism in acute myeloid leukemia stem cells

2023· article· en· W4362593963 on OpenAlexaff
Vincent Rondeau, Rachel Culp‐Hill, Cristiana O’Brien, Jacob M. Berman, Julie A. Reisz, Duhan Yendi, Tianyi Ling, Soheil Janangiri, Anastasia N. Tikhonova, Angelo D’Alessandro, Courtney L. Jones

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsHaematopoiesisMyeloid leukemiaStem cellArginineProgenitor cellLeukemiaPopulationCancer researchMyeloidBiologyBone marrowImmunologyMedicineCell biologyBiochemistryAmino acid

Abstract

fetched live from OpenAlex

Abstract Acute myeloid leukemia (AML) is a devastating hematologic malignancy diagnosed in over 20,000 patients each year in the United States. The five-year survival rate in adult AML is less than 30%, highlighting the need for novel therapies to treat this malignancy. Current therapeutic approaches fail in part due of their inability to fully eradicate the disease-initiating leukemia stem cells (LSCs). Our previous work and the work of many others has demonstrated that LSCs have unique metabolic dependencies compared to the more differentiated AML blasts population. Importantly, these metabolic differences can be targeted to specifically eradicate the LSC population. To date, limited studies have examined the difference in metabolism between human LSCs and their normal counterparts, hematopoietic stem cells (HSCs), at the level of individual metabolites. To address this gap in our knowledge, we performed an unbiased mass spectrometry-based metabolomics analysis hematopoietic stem and progenitor cells (HSPCs) enriched from the bone marrow of 7 healthy donors and LSCs enriched from 18 primary AML patient specimens. This analysis revealed 38 metabolites that were significantly different between LSCs and HSPCs (FDR<0.05) including several amino acids, nucleotides, and TCA cycle intermediates. Pathway analysis revealed that the most significantly enriched pathways between LSCs and HSPCs is arginine biosynthesis (FDR =9.99 × 10−14). To determine if arginine is functionally important for LSCs biology we cultured LSCs and HSCs in arginine depleted media and measured colony forming potential which showed that arginine depletion targeted LSCs without harming HSPCs. Arginine metabolism has been widely studied in cancer, including AML, and shown to be essential for urea cycle function, polyamine synthesis, pyrimidine synthesis, and creatine metabolism. In contrast to preclinical studies, clinical trials evaluating safety and efficacy of arginine-depleting therapies in relapsed AML (NCT02899286, NCT02732184, NCT01910012) have shown limited efficacy. This is likely because cancer cells upregulate arginine biosynthesis upon arginine depletion therapy. Therefore, we hypothesized that targeting metabolic pathways downstream of arginine may have more clinical benefit. To determine what metabolic pathways arginine contributes to in LSCs, we performed tracing analysis using uniformly labeled 13C15N arginine. LSCs were enriched from primary AML specimens and incubated 100µM with L-arginine-13C6,15N4 hydrochloride for 1, 6, 12, and 24 hours. Mass spectrometry, analysis revealed that arginine is metabolized through the urea cycle (ornithine) into polyamines (putrescine, spermidine, and spermine). While polyamine metabolism has been explored in several cancer types, its role in AML LSCs is unknown. Therefore, we sought to examine the importance of polyamines in AML and LSCs by depleting polyamines from cells using DENSpm, a potent inducer of SAT1, which is responsible for spermidine and spermine acetylation, resulting in their cellular export. We observed decreased polyamine concentration and overexpression of SAT1 in AML cell lines following DENSpm treatment. Importantly, DENSpm treatment resulted in decreased viability and colony forming potential of LSCs enriched from 12 primary AML specimens but did not harm normal human HSPCs. To determine if polyamine depletion alters the function of LSC or HSPCs we measured engraftment of primary AML and healthy bone marrow into immune deficient mice, which is considered the gold-standard for assessing stem cell function. DENSpm treatment resulted in a significant decrease in engraftment in 4 primary AML specimens but did not alter engraftment levels of a normal bone marrow specimen. Finally, to determine if targeting polyamine metabolism in AML is a clinically relevant approach, we transplanted mice with primary human AML, treated the mice with 60mg/kg DENSpm for 2 weeks, and measured leukemic burden. Leukemia burden in the bone marrow was significantly decreased upon DENSpm treatment compared to vehicle treated mice. Overall, these data suggest that polyamine metabolism represents a metabolic target in LSCs. Finally, we sought to explore the molecular mechanisms by which polyamine levels are essential for LSCs but not HSPCs. To do this, we performed RNA-sequencing on LSCs and HSPCs treatment with DENSpm for 24 hours and performed gene set enrichment analysis. These data revealed that protein translation gene sets were altered in LSCs but not HSPCs. Interestingly, the polyamine spermidine regulates protein translation through its role as a precursor of hypusine, an essential modification of eIF5A. We determined that polyamine depletion through DENSpm treatment decreased hypusination of eIF5A by western blot, which was rescued by co-treatment with exogenous spermidine. Further, DENSpm treatment resulted in a decrease in protein synthesis which was determine by measuring OP-Puro incorporation. Importantly, protein synthesis was also rescued by co-treatment with spermidine. Overall, these data suggest that DENSpm reduces protein synthesis through decreased hypusination of eIF5A, resulting in effective targeting of human LSCs. Citation Format: Vincent Rondeau, Rachel Culp-Hill, Cristiana O’Brien, Jacob Berman, Julie A. Reisz, Duhan Yendi, Tianyi Ling, Soheil Janangiri, Anastasia Tikhonova, Angelo D’Alessandro, Courtney Jones. Targeting polyamines metabolism in acute myeloid leukemia stem cells. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr NG07.

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 score0.006

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)0.0020.001

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 head0.039
GPT teacher head0.351
Teacher spread0.312 · 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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