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Enregistrement W4310106485 · doi:10.1182/blood-2022-170366

Metformin Treatment Abrogates the Competitive Advantage of <i>Dnmt3a</i> R878H HSPCs By Enhancing DNA Methylation Activity

2022· article· en· W4310106485 sur OpenAlexaff
Mohsen Hosseini, Séverine Cathelin, Alex C.H. Liu, Yitong Yang, Amit Subedi, Dhanoop Manikoth Ayyathan, Shraddha Pai, Steven M. Chan

Notice bibliographique

RevueBlood · 2022
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueEpigenetics and DNA Methylation
Établissements canadiensUniversity of TorontoOccupational Cancer Research CentrePrincess Margaret Cancer CentreUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésBiologyHaematopoiesisProgenitor cellDNA methylationGene knockdownMetforminMethylationCancer researchStem cellMolecular biologyCell biologyDNAGeneticsGeneGene expression

Résumé

récupéré en direct d'OpenAlex

Clonal hematopoiesis of indeterminate potential (CHIP) refers to the clonal expansion of hematopoietic stem and progenitor cells (HSPCs) carrying leukemogenic mutations in individuals without evidence of a blood disorder. CHIP carriers are at an increased risk of blood cancers and cardiovascular diseases. Targeting the clonal expansion of mutant HSPCs has the potential to mitigate CHIP-related illnesses. The most commonly mutated gene in CHIP is DNMT3A, which encodes an enzyme that catalyzes the methyl transfer from S-adenosylmethionine (SAM) to cytosines in DNA. The heterozygous DNMT3A hotspot mutation at R882 exerts a dominant negative effect on the wild-type (WT) allele, resulting in decreased DNA methylation activity. Prior studies have shown that murine HSPCs carrying mutant Dnmt3a R878H (equivalent to R882 in humans) have an advantage over WT cells in competition assays. Here, we aimed to first identify differences in the functional properties between Dnmt3a-mutated and WT HSPCs. Given the crosstalk between mitochondrial metabolism and DNA methylation, we investigated potential differences in mitochondrial activity and found that the level of mitochondrial respiration was higher in Dnmt3aR878H/+ HSPCs than in WT cells. To determine if this translated to differential dependencies, we silenced the expression of critical subunits in the each of five electron transport chain (ETC) complexes. Knockdown of NDUFV1 in Complex I was the most effective in reducing the competitive advantage of Dnmt3aR878H/+ cells in vitro. To explore translational relevance of this finding, we tested the impact of metformin, a pharmacologic inhibitor of Complex I, on Dnmt3a-mutated HSPCs. Treatment with metformin at clinically relevant concentrations suppressed the competitive advantage of mutant cells in vitro. Importantly, this effect was rescued by expression of NDI1, a metformin-resistant yeast analog of Complex I. To extend these findings, we conducted a competitive repopulation assay between CD45.2+ Dnmt3aR878H/+ and CD45.1+ Dnmt3a+/+ HSPCs. Metformin treatment abrogated the in vivo competitive advantage of mutant cells over an 8-month period based on peripheral blood chimerism. To decipher the mechanism of action, we performed transcriptome and metabolome profiling of mutant HSPCs treated with or without metformin for 1 month. GSEA analysis of the transcriptome data revealed a downregulation of genes associated with stemness in metformin-treated cells. Intriguingly, we found that metformin increased the expression of genes involved in one-carbon metabolism, which generates SAM. Consistent with these findings, metabolomics analysis showed that the levels of several key metabolites in one-carbon metabolism, including SAM, were higher in metformin-treated cells compared with controls. Genetic and pharmacologic inhibition of serine hydroxymethyltransferase 2 (SHMT2), a key enzyme in one-carbon metabolism, as well as the addition of exogeneous S-adenosylhomocysteine (SAH), an inhibitor of SAM-dependent methyltransferases, effectively rescued the effect of metformin on mutant cells in vitro. Based on the above findings, we hypothesized that metformin treatment might enhance the residual DNA methylation activity found in Dnmt3aR878H/+ mutated cells by increasing SAM concentration. In support of this hypothesis, we found that exogeneous SAM reproduced the effect of metformin, and HSPCs with homozygous Dnmt3aR878H mutations were insensitive to metformin. Furthermore, we performed DNA methylome profiling of untreated and metformin-treated mutant and WT HSPCs using RRBS. This analysis revealed that the hypomethylated regions (HMRs) in untreated Dnmt3aR878H/+ HSPCs relative to WT controls were enriched for regions of repressed chromatin with H3K27 methylation. Importantly, metformin treatment increased the level of DNA methylation at these regions in mutated HSPCs. In summary, our findings demonstrate that Dnmt3aR878H/+ HSPCs depend on ETC activity and particularly complex I activity to maintain their competitive advantage over WT cells. We propose a model in which inhibition of complex I activity with metformin increases one-carbon metabolism and SAM level, thereby restoring DNA methylation at HMRs and the differentiation of mutant HSPCs. Our findings have important implications for the development of preventive interventions against DNMT3A-mutated CHIP.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,008

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,007
Tête enseignante GPT0,244
Écart entre enseignants0,237 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2022
Routes d'admission1
Résumé présentoui

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