scholarly journals Molecular dysfunctions in acute myeloid leukemia revealed by integrated analysis of microRNA and transcription factor

2016 ◽  
Vol 48 (6) ◽  
pp. 2367-2380 ◽  
Author(s):  
XIAO-CONG LIN ◽  
YONG XU ◽  
GUO-PING SUN ◽  
JIN-LI WEN ◽  
NING LI ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Transcription Factor ◽  
Myeloid Leukemia ◽  
Integrated Analysis ◽  
Acute Myeloid

scholarly journals NUP-98 Rearrangements Led to the Identification of Candidate Biomarkers for Primary Induction Failure in Pediatric Acute Myeloid Leukemia

2021 ◽  
Vol 22 (9) ◽  
pp. 4575
Author(s):  
Vincenza Barresi ◽  
Virginia Di Bella ◽  
Nellina Andriano ◽  
Anna Provvidenza Privitera ◽  
Paola Bonaccorso ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Mutational Analysis ◽  
Integrated Analysis ◽  
Induction Phase ◽  
Pediatric Acute Myeloid Leukemia ◽  
Expression Arrays ◽  
Primary Induction ◽  
Induction Failure ◽  
Acute Myeloid

Conventional chemotherapy for acute myeloid leukemia regimens generally encompass an intensive induction phase, in order to achieve a morphological remission in terms of bone marrow blasts (<5%). The majority of cases are classified as Primary Induction Response (PIR); unfortunately, 15% of children do not achieve remission and are defined Primary Induction Failure (PIF). This study aims to characterize the gene expression profile of PIF in children with Acute Myeloid Leukemia (AML), in order to detect molecular pathways dysfunctions and identify potential biomarkers. Given that NUP98-rearrangements are enriched in PIF-AML patients, we investigated the association of NUP98-driven genes in primary chemoresistance. Therefore, 85 expression arrays, deposited on GEO database, and 358 RNAseq AML samples, from TARGET program, were analyzed for “Differentially Expressed Genes” (DEGs) between NUP98+ and NUP98-, identifying 110 highly confident NUP98/PIF-associated DEGs. We confirmed, by qRT-PCR, the overexpression of nine DEGs, selected on the bases of the diagnostic accuracy, in a local cohort of PIF patients: SPINK2, TMA7, SPCS2, CDCP1, CAPZA1, FGFR1OP2, MAN1A2, NT5C3A and SRP54. In conclusion, the integrated analysis of NUP98 mutational analysis and transcriptome profiles allowed the identification of novel putative biomarkers for the prediction of PIF in AML.

scholarly journals The ETO Protein Disrupted in t(8;21)-Associated Acute Myeloid Leukemia Is a Corepressor for the Promyelocytic Leukemia Zinc Finger Protein

2000 ◽  
Vol 20 (6) ◽  
pp. 2075-2086 ◽  
Author(s):  
Ari M. Melnick ◽  
Jennifer J. Westendorf ◽  
Adam Polinger ◽  
Graeme W. Carlile ◽  
Sally Arai ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Transcription Factor ◽  
Zinc Finger ◽  
Transcriptional Repression ◽  
Histone Deacetylases ◽  
Myeloid Leukemia ◽  
Histone Deacetylase Inhibitors ◽  
Promyelocytic Leukemia ◽  
Promyelocytic Leukemia Zinc Finger ◽  
Acute Myeloid

ABSTRACT The ETO protein was originally identified by its fusion to the AML-1 transcription factor in translocation (8;21) associated with the M2 form of acute myeloid leukemia (AML). The resulting AML-1–ETO fusion is an aberrant transcriptional regulator due to the ability of ETO, which does not bind DNA itself, to recruit the transcriptional corepressors N-CoR, SMRT, and Sin3A and histone deacetylases. The promyelocytic leukemia zinc finger (PLZF) protein is a sequence-specific DNA-binding transcriptional factor fused to retinoic acid receptor α in acute promyelocytic leukemia associated with the (11;17)(q23;q21) translocation. PLZF also mediates transcriptional repression through the actions of corepressors and histone deacetylases. We found that ETO is one of the corepressors recruited by PLZF. The PLZF and ETO proteins associate in vivo and in vitro, and ETO can potentiate transcriptional repression by PLZF. The N-terminal portion of ETO forms complexes with PLZF, while the C-terminal region, which was shown to bind to N-CoR and SMRT, is required for the ability of ETO to augment transcriptional repression by PLZF. The second repression domain (RD2) of PLZF, not the POZ/BTB domain, is necessary to bind to ETO. Corepression by ETO was completely abrogated by histone deacetylase inhibitors. This identifies ETO as a cofactor for a sequence-specific transcription factor and indicates that, like other corepressors, it functions through the action of histone deactylase.

The oligodendrocyte lineage transcription factor 2 (OLIG2) is epigenetically regulated in acute myeloid leukemia

2017 ◽  
Vol 55 ◽  
pp. 76-85.e3
Author(s):  
Arzu Yalcin ◽  
Marlon Kovarbasic ◽  
Julius Wehrle ◽  
Rainer Claus ◽  
Heiko Becker ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Transcription Factor ◽  
Myeloid Leukemia ◽  
Acute Myeloid

The GATA2 transcription factor directly binds and activates MYB expression in acute myeloid leukemia

2015 ◽  
Vol 43 (9) ◽  
pp. S58
Author(s):  
Xabier Cortés-Lavaud ◽  
Carmen Vicente ◽  
Leire Urquiza ◽  
Marcos González ◽  
María J. Calasanz ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Transcription Factor ◽  
Myeloid Leukemia ◽  
Acute Myeloid

scholarly journals A three-gene signature might predict prognosis in patients with acute myeloid leukemia

2020 ◽  
Vol 40 (6) ◽  
Author(s):  
Xin Zhu ◽  
Qian Zhao ◽  
Xiaoyu Su ◽  
Jinming Ke ◽  
Yunyun Yi ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Transcription Factor ◽  
High Risk ◽  
Myeloid Leukemia ◽  
Cox Regression ◽  
Risk Group ◽  
White Blood Cells ◽  
Gene Signature ◽  
Low Risk ◽  
Acute Myeloid

Abstract The identification of effective signatures is crucial to predict the prognosis of acute myeloid leukemia (AML). The investigation aimed to identify a new signature for AML prognostic prediction by using the three-gene expression (octamer-binding transcription factor 4 (OCT4), POU domain type 5 transcription factor 1B (POU5F1B) and B-cell-specific Moloney murine leukemia virus integration site-1 pseudogene 1 (BMI1P1). The expressions of genes were obtained from our previous study. Only the specimens in which three genes were all expressed were included in this research. A three-gene signature was constructed by the multivariate Cox regression analyses to divide patients into high-risk and low-risk groups. Receiver operating characteristic (ROC) analysis of the three-gene signature (area under ROC curve (AUC) = 0.901, 95% CI: 0.821–0.981, P&lt;0.001) indicated that it was a more valuable signature for distinguishing between patients and controls than any of the three genes. Moreover, white blood cells (WBCs, P=0.004), platelets (PLTs, P=0.017), percentage of blasts in bone marrow (BM) (P=0.011) and complete remission (CR, P=0.027) had significant differences between two groups. Furthermore, high-risk group had shorter leukemia-free survival (LFS) and overall survival (OS) than low-risk group (P=0.026; P=0.006), and the three-gene signature was a prognostic factor. Our three-gene signature for prognosis prediction in AML may serve as a prognostic biomarker.

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