Deregulation of Transcription Factors GATA-1, GATA-2 and C/EBPa in Acute Promyelocytic Leukemia.
Notice bibliographique
Résumé
Abstract Acute promyelocytic leukemia (APL) accounts for ~10% of all acute myelogenous leukemia (AML) cases, and is characterized by accumulation of abnormal promyelocytes in the bone marrow. APL is uniquely associated with balanced chromosomal translocations involving the retinoic acid receptor alpha (RARA) locus. A functional chimeric protein, X-RARA, is created, whose N-terminus is derived from the partner (“X”) gene, and retains its oligomerization domain. The C-terminus is derived from RARA. X-RARA contributes to the APL phenotype by interfering with granulocyte differentiation, through acquisition of novel transactivating activity and/or interference with the normal functions of RARA and X. Several studies have indicated that defective retinoid signaling, though sufficient to block myeloid differentiation, cannot induce a leukemia. Thus, pathways external to retinoid signaling must be deregulated by X-RARA in order to give rise to APL. We previously reported whole genome gene expression analysis of the hCG-NuMA-RARA transgenic mouse model (Sukhai et al, Blood, Blood, 2006: a2247), and that the NuMA-RARA fusion protein deregulated a wide array of hematopoietic and myeloid transcription factors in leukemic cells derived from transgenic mice. Here, we report that the deregulated expression of this transcription factor set (specifically, Gata-1, Gata-2, C/ebpa and Pu.1) accurately distinguished leukemic TM mice from WT animals, and was dependent upon both the presence of functional RXRA (Sukhai et al, Oncogene, 2008) and transgene dosage. We thus formulated the hypothesis that NuMA-RARA initiated the deregulation of a range of transcription factors, which in turn were responsible for deregulating pathways within the cell. In order to determine whether this transcription factor signature was unique to APL, we focused on GATA-1, GATA-2, PU.1 and C/EBPA, and examined their expression in a range of AML cell lines. Strikingly, the over-expression of GATA-1 was unique to APL cell lines and the OCI/AML4 cell line. GATA-2 was over-expressed in most cell systems tested, suggesting that its up-regulation may play a general role in leukemogenesis. C/EBPA was under-expressed in NB4 cells specifically, while PU.1 was not significantly deregulated in any cell system tested. Having identified that APL cell lines recapitulated our observation of deregulated myeloid transcription factor expression in transgenic mice, we sought to extend these studies to human patients. We analyzed the expression of GATA- 1, GATA-2, PU.1 and C/EBPA in a series of 12 APL patients, 10 AML patients with a range of diagnoses, and 12 normal BM samples. We observed specific up-regulation of GATA-1 (2.0–20.0-fold change, 7/12 patients) and GATA-2 (2.0–25.0-fold change, 9/12 patients) and under-expression of C/EBPA (0.05–0.5-fold change, 11/12 patients), in APL, but not AML, patient samples, in comparison to normal BM. The deregulated expression of these three transcription factors could accurately distinguish APL patient samples from AML and normal BM in both principle component analysis and hierarchical clustering analysis. We therefore report herein that NuMA-RARA deregulated a wide array of myeloid transcription factors, suggesting that a state of globally deregulated myeloid transcription exists in APL cells. Furthermore, a specific subset of transcription factors, GATA-1, GATA-2 and C/EBPA, can be used to specifically classify APL patient samples. These deregulated transcription factors may therefore serve as potential therapeutic targets and a means of distinguishing APL from other forms of acute myelogenous leukemia.
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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 ».