IDH2 R172 Mutations Define a Unique Subgroup of Patients in Angioimmunoblastic T-Cell Lymphoma
Notice bibliographique
Résumé
Abstract Background: Angioimmunoblastic T-cell lymphoma (AITL) is a common subtype of peripheral T-cell lymphoma (PTCL) with distinct pathological features and poor prognosis. Currently used chemotherapy is mostly unsuccessful with a 3-year overall survival of less than 30%. We and others have identified frequent mutations affecting IDH2 at arginine-172 (R172),TET2, DNMT3A and RHOA in AITL. The biochemical and functional consequences of IDH2R172 mutations in T cells have not been demonstrated. In this study, we performed targeted re-sequencing of epigenetic regulators, including IDH2, TET2 and DNMT3A in molecularly defined PTCL cases and analyzed the biochemical changes associated with IDH2R172 mutations as well as alterations in gene expression profiling (GEP), DNA methylation and histone modification that may improve our understanding of the pathogenetic mechanisms in AITL. Methods: We performed targeted re-sequencing of epigenetic regulators IDH2, TET2 and DNMT3A in AITL (n = 39) and PTCL subtypes (n = 53) with corresponding GEP. Due to lack of appropriate cell lines derived from AITL, we chose to use Jurkat T cells, a T-ALL cell line frequently used for T-cell functional studies and normal CD4+T cell to study the biochemical consequences of IDH2R172 mutations in T-cells. Liquid chromatography- tandem mass spectrometry was utilized for the detection of intracellular level of the 2-hydroxyglutarate and levels of 5-methycytosine and 5-hydroxymethycytosine in genomic DNA. Alterations of histone lysine tri-methylation were assessed by immunohistochemistry in AITL specimens and western blotting in vitro. Results: TET2 mutations appear to be the founder mutations in AITL with 82.1% (32/39) mutated cases and present as the major clone in the majority of mutant cases (75%; 24/32). TET2 mutations were also observed at a lower frequency in PTCL-NOS molecular subgroups (TBX21 (46%; 10/18); GATA3 (41%; 5/12)) and ALK negative-ALCL (33.3%, 4/12). The mutations in DNMT3A were observed at similar frequency in AITL (38.5%, 15/39) and PTCL-NOS subgroups [TBX21 (33%; 6/18); GATA3 (25%; 3/12)). However, IDH2R172 mutations were found predominantly in AITL (33.3%, 13/39), but rarely in PTCL-NOS subgroups (6.7%, 1/15 in PTCL-NOS). Remarkably, IDH2R172 mutant cases formed a unique cluster in unsupervised hierarchical clustering, and IDH2R172mutation defined a unique subset within AITL with a distinct gene expression signature. We observed that ectopic expression of IDH2R172K in the Jurkat T cell line led to a markedly increased level of intracellular 2-HG and up-regulation of the repressive histone methylation mark H3K27me3. Furthermore, a significant increase in 5-methylcytosine and corresponding decrease in 5-hydroxymethycytosine in genomic DNA was also observed in IDH2R172K transduced Jurkat and primary CD4+ T cells. Consistent with these findings, significant increase in aglobal DNA hypermethylation in proximal promoter regions and a global increase of the repressive histone mark H3K27me3 was observed in AITL harboring IDH2R172 mutants. Integrative analysis of GEP and promoter methylation identified several recurrently hypermethylated genes including negative regulators of the NF-kB pathway. Conclusion: IDH2R172 mutations define a unique subgroup of patients in angioimmunoblastic T-cell lymphoma with a distinct gene expression profile. IDH2R172 mutations are associated with global promoter hypermethylation in genomic DNA and trimethylation of H3K27 in AITL specimens. The current findings suggest that abnormal methylation associated with IDH2R172 mutations contribute to lymphomagenesis in AITL. Disclosures Fu: Nanostring: The author is a potential inventor on a patent application using Nanostring technology for the Lymph2Cx assay, which has been licensed from the NIH by Nanostring Patents & Royalties. Greiner:Nanostring: The author is a potential inventor on a patent applicaiton using Nanostring technology for a different assay, which has been licensed from the NIH by Nanostring Patents & Royalties.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| 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) | 0,000 | 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 tête enseignante, 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 ».