MétaCan
Menu
Retour à la cohorte
Enregistrement W2911359328 · doi:10.1158/2326-6074.cricimteatiaacr18-b170

Abstract B170: Therapeutic implications of altered epigenetics and DNA damage responses in IDH2-mutated hematologic diseases

2019· article· en· W2911359328 sur OpenAlexaff
Julie Leca

Notice bibliographique

RevueCancer Immunology Research · 2019
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensOntario Institute for Cancer Research
Organismes subventionnairesnon disponible
Mots-clésIDH2EpigeneticsCancer researchBiologyMyeloidDNA methylationHistoneMyeloid leukemiaIDH1HaematopoiesisMutationStem cellGeneticsGeneGene expression

Résumé

récupéré en direct d'OpenAlex

Abstract Acute myeloid leukemia (AML) and angioimmunoblastic T-cell lymphoma (AITL), are hematologic diseases requiring novel approaches to patient selection and therapy. In AITL, neoplastic cells express many markers of T follicular helper (TFH) cells, while in AML, myeloid stem and progenitor cells are affected. Tumor cells of AML and AITL patients frequently bear mutations affecting genes involved in epigenetic regulation, including isocitrate dehydrogenase (IDH) and ten-eleven translocation-2 (TET2). IDH mutations drive production of the rare metabolite D-2-hydroxyglutarate (2HG), which competitively inhibits α-ketoglutarate (α-KG)-dependent dioxygenases such as the TET proteins (affecting DNA methylation) and Jumonji histone demethylases (altering histone methylation). IDH mutations occur in 30% of AML and AITL cases but the spectrum of these mutations differs. In AML, IDH1R132 (41%), IDH2R140 (44%) and IDH2R172 (15%) dominate, and IDH and TET2 mutations are mutually exclusive. In AITL, IDH2R140 (2%) and IDH2R172 (98%) dominate (no IDH1 mutations), with co-mutation of TET2 in 82.1% of cases. In AML, loss of these dioxygenase activities causes epigenetic alterations to DNA and histones, leads to abnormal gene transcription that affects hematopoietic cell differentiation, and drives myeloid disease. However, in AITL disease, the impact of the IDH2 mutation is completely unknown. My goal is to dissect the effects of IDH2 and TET2 mutations in hematologic diseases to understand how IDH2 and TET2 mutations collaborate to drive malignancy in AITL, and why they cooperate differently in myeloid and lymphoid diseases. I focus on DDR signaling and epigenetics analysis to found novel therapeutic vulnerabilities arise from the altered epigenetic regulation and DDR linked to IDH2 and TET2 mutations. I used a CD4-Cre mouse model to introduce the IDH2R172K and TET2 mutations in the T-cell compartment. This would allow me to study the collaboration between IDH2 and TET2 mutations in the context of T-cells. Mice bearing both IDH2 and TET2 mutations show decreased survival, with a median survival of approximately 8 months accompanied by splenomegaly and lymphadenopathy. This is significantly different than CD4+ control mice or single mutant mice. Double mutant mice (DM) present a disruption of spleen and lymph node architecture. To understand this phenotype, I performed comprehensive flow cytometry staining and, surprisingly, I found that the increased spleen size is not due to T-cell infiltration, but is due to increased erythropoiesis and expansion of immature erythropoietic cells (CD71+, cKit+). We can explain this result by the fact that CD4-Cre is also expressed in some progenitor cells leading to stress induced erythropoiesis. However, if we focus on the T-cell population, we see that DM mice present a T-cell phenotype including a decrease of CD4+ naïve cells and an increase of CD4+ effector memory cells as early as 5 months. So, there is an imbalance in T-cell homeostasis, but only when both the IDH2 and TET2 mutations are present, suggesting a cooperative role for both mutations in T-cell development. Since both IDH2 and TET2 affect epigenetic regulation, I want to conduct experiments to understand how these changes modulate T-cells homeostasis. Moreover, emerging data support the hypothesis that connections exist between epigenetic regulators and DDR signaling in hematologic diseases. My final aim will be to attempt to evaluate the efficacy of treatment with IDH2 inhibitors, hypomethylating agents, or DDR-targeting drugs, alone or in combination in AITL disease and identify factors involved in responses to these therapies or in the development of resistance. Finally, I will compare results obtained in AML versus AITL mouse models and clinical samples to identify mechanisms that are shared, and those that are unique to each disease. Citation Format: Julie Leca. Therapeutic implications of altered epigenetics and DNA damage responses in IDH2-mutated hematologic diseases [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B170.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,598
Score d'incertitude au seuil0,719

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,082
Tête enseignante GPT0,422
Écart entre enseignants0,340 · 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 tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
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

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueCancer Immunology ResearchMême sujetAcute Myeloid Leukemia ResearchTravaux en français237 207