PKM2 modulation regulates leukemia cell survival.
Notice bibliographique
Résumé
Abstract Acute myeloid leukemia (AML) is characterized by an aberrant metabolic phenotype in which cells rely on aerobic glycolysis (AG) to fuel anabolic processes. Altered glycolytic genes such as pyruvate kinase (PK) are partially responsible for these metabolic changes and are therefore potential novel anti-AML targets. PK is the final rate limiting enzyme in glycolytic metabolism, catalyzing the transfer of an inorganic phosphate from phosphoenolpyruvate to adenosine diphosphate (ADP), yielding one molecule of adenosine triphosphate (ATP) and pyruvate. In AML, the tetrameric and high activity PKM1 isoform of PK is predominately replaced by the dimeric and low activity PKM2 isoform. This conversion toward PKM2 decreases pyruvate production to fuel the tricarboxylic acid (TCA) cycle and instead leads to an accumulation of upstream glycolytic intermediates that are diverted to anabolic pathways to sustain rapid proliferation. In addition to its metabolic role, dimeric PKM2 is a protein kinase and facilitates transcriptional regulation by accumulating in the nucleus and acting as a transcriptional co-activator. To first understand the role of PKM2, protein levels were profiled. PKM2 was significantly increased (70-fold, p<0.01) compared to PKM1 in AML cell lines and is elevated in patient-derived AML cells over normal cells; protein increases were correlated with reduced PKM2 enzymatic activity. To understand the functional role, lentiviral mediated transduction techniques created cell lines with reduced PKM2 (denoted hereafter as PKM2-/-). Genetic inhibition of PKM2 reduced PK activity, cell proliferation and clonogenic growth. Immunocompromised mice injected with PKM2-/- cells lived significantly longer than those injected with endogenous PKM2. Therefore, PKM2 is as a selective and reasonable target for AML therapy. A high throughput screen identified plumbagin (PLB) as a cytotoxic compound (IC50=1.40 – 2.73µM) with specific activity towards PKM2. PLB increases PKM2, but not PKM1, activity and selectively increases PK activity in patient-derived AML cells. To confirm the molecular target, immunoprecipitation and GC-MS analysis detected PLB only in PKM2-rich fractions; PKM2 protein's thermal stability also shifted in the presence of PLB, confirming a molecular interaction. In vitro, PLB selectively reduced viability and clonogenic growth of patient-derived AML cells with no effects on healthy hematopoietic cells. In vivo, treatment of PLB (2.5mg/kg, 3 times per week over five weeks) selectively reduced AML cell engraftment by approximately 85% with no changes in biotoxicity markers; no change in engraftment was noted when mice were injected with normal hematopoietic cells. To reconcile observations that decreased andincreased PKM2 activity imparted anti-AML phenotypes, a direct comparative approach was employed to determine the downstream impact of PKM2 modulation. In vitro studies confirmed that cell death following decreased and increased activity was attributed to disruption of the native oligomeric state that impaired dimeric PKM2 nuclear translocation. By decreasing nuclear translocation, there was a decrease in transcriptional regulation resulting in decreased expression of c-Myc, a well-established oncogenic transcription factor upregulated in AML linked to glutamine dependency and increased proliferation. Indeed, PKM2-/- and PLB-treated cells had reduced nuclear PKM2 accumulation (p<0.05), decreased c-Myc expression (p<0.05), reduced glutaminase (GLS-1) expression (p<0.5) and reduced glutamine uptake(p<0.05). In summary, activation or inhibition of PKM2, through reduced levels of dimeric protein, lead to selective leukemia cell death in vitro and in vivo. Understanding the mechanism by which similar cell fates arise from opposing cellular pathways highlights the pivotal role of PKM2 governing cancer cell survival, and supports PKM2 as a promising therapeutic target in AML as well as PLB as a novel and potent pharmacological agent.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».