A 14q32.31 Genomic-Imprinted DLK1-DIO3 microrna promotes Leukemogenesis By Inducing Stem Cell Quiescence and Inhibiting NK Cell Anti-Cancer Immunity
Notice bibliographique
Résumé
Leukemia emergence, maintenance, relapse and/or progression are causally linked to the presence of drug-resistant leukemia-initiating cells and impaired natural killer (NK) cell anti-tumor immune-response. Bone marrow microenvironment (BMM)- and/or leukemia-derived signals induce aberrant non-coding RNA expression and inhibit protein phosphatase 2A (PP2A) tumor suppressor activity. PP2A loss-of-function is essential for NK cell activity and leukemic but not normal stem and progenitor cell proliferation and survival. The human MIR300 gene is an intergenic miRNA that belongs to the 14q32.31 DLK1-DIO3 genomic-imprinted tumor suppressor miRNA cluster B. MIR300 was found involved in loss-of heterozygosity, inhibited in several tumor types with high mitotic index and during epithelial-to-mesenchymal transition (EMT), and associated with a cancer stem cell phenotype. By using primary cells from Philadelphia-positive (Ph+) chronic myelogenous leukemia (CML) in chronic (CP) and blastic (BC) phase, and complex karyotype (CK) acute myeloid leukemia (AML) patients, as paradigmatic examples of stem cell-derived neoplasms characterized by constitutive expression of oncogenic kinases, PP2A loss-of-function, altered microRNA expression and impaired NK cell proliferation and cytotoxicity, we found that MIR300 is a cell context-independent tumor suppressor with anti-proliferative and PP2A-dependent pro-apoptotic activities which are sequentially activated in a MIR300 dose-dependent manner through inhibition of CCND2/CDK6 and SET (PP2A inhibitor), respectively. To prevent PP2A-induced apoptosis, MIR300 is inhibited by oncogenic signals in CD34+CML (CP and BC) and CK-AML progenitors. Conversely, tumor-naïve BMM-induced C/EBPbeta-mediated signals (hypoxia and MSC exosomes) markedly upregulate MIR300 expression in primary CML and AML CD34+CFSEmax leukemic stem (LSC) and CD56+CD3-NK cells to induce/maintain quiescence (increased CD34+leukemic blasts in G0) and impair immune-response (suppression of NK cell proliferation and cytotoxic activity toward CD34+ leukemic blasts and CFSEmaxCD34+ CML-BC quiescent LSCs), respectively. Inhibition of MIR300 expression/activity rescues NK cell proliferation and anti-tumor cytotoxicity and prevented MSC- and hypoxia-induced growth-suppression of CD34+leukemic blasts by inhibiting degradation of MIR300 targets (e.g. SET, CCND2). We found that CML and AML LSCs escape MIR300-induced PP2A-mediated apoptosis through the hypoxia- and tumor-dependent TGFb1-FoxM1-mediated upregulation of TUG1 lncRNA. TUG1 is an oncogenic lncRNA described as a MIR300sponge and found upregulated in solid tumors, in which it has strong diagnostic, prognostic and therapeutic relevance and is associated with cancer stem cell maintenance and EMT. In quiescent CML and AML LSCs, TUG1 uncouples and limits MIR300 tumor suppressor functions to cytostasis by maintaining unbound MIR300 at levels sufficient to inhibit CCND2 and CDK6 but not SET expression. Exposure to clinically-relevant CpG-modified oligonucleotides modulating MIR300levels and/or inhibiting TUG1 MIR300-sponging activity, restores NK cell proliferation and cytotoxic activity, and suppresses human leukemic but not normal hematopoiesis by eradicating nearly all (> 95% reduction) CFSEmaxCD34+ and CD45+CD34+CD38-CD90+ LSCs and CD34+leukemic CML (CP and BC) and CK-AML blasts in vitro (CFCs, LTC-IC, and CFSEmaxCD34+cell tracking) and/or in NRG-SGM3 PDX mouse models of acute and chronic myeloid leukemias. Altogether, this work highlights the therapeutic importance of altering MIR300 expression in anti-LSC and NK cell-based approaches for myeloid leukemias, and indicates that tumor-naïve BMM-induced MIR300 tumor suppressor anti-proliferative and PP2A-activating functions may support leukemogenesis by promoting the formation and initial expansion of the quiescent LSC pool through the induction of LSC dormancy and inhibition of quiescent LSC killing by cytokine-activated NK cells, respectively. (G.S. and R.T. equally contributed to this work) Disclosures Stagno: BMS: Honoraria; Incyte: Honoraria; Pfizer: Honoraria; Novartis: Honoraria. Deininger:TRM: Consultancy; Sangoma: Consultancy; Incyte: Honoraria; Novartis: Honoraria; Sangamo: Consultancy; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Humana: Honoraria; Ascentage Pharma: Consultancy, Honoraria; Blueprint: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Honoraria, Research Funding; Fusion Pharma: Consultancy; Adelphi: Consultancy. Milojkovic:BMS: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Incyte: Honoraria, Speakers Bureau; Pfizer: Honoraria, Speakers Bureau. Apperley:Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Baer:Takeda: Research Funding; Incyte: Research Funding; Kite: Research Funding; Forma: Research Funding; AI Therapeutics: Research Funding; Abbvie: Research Funding; Astellas: Research Funding.
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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
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 ».