Therapy-induced PML nuclear body re-formation and p53 activation trigger acute promyelocytic leukaemia cure
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE51723 | GEO | 2014/01/11
SECONDARY ACCESSION(S): PRJNA224733
REPOSITORIES: GEO
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Project description:The therapy-induced PML/RARA catabolism elicits the loss of APL-initiating cell self-renewal through PML NB reformation and P53 activation. These results explain the curative activity of the RA/arsenic combination, the resistance to RA of PLZF/RARA-driven APLs and they raise the prospect that activation of this PML/P53 checkpoint might have therapeutic values in other malignancies. Gene expression profiles of 36 transgenic induced APL and 36 viral transduction APL were hybridized using Affymetrix Mouse Gene 1.0 ST Arrays
2014-01-11 | E-GEOD-51723 | biostudies-arrayexpress
Project description:Retinoic acid (RA) and arsenic target the PML/RARA driver of Acute Promyelocytic Leukemia (APL), their combination now curing over 95% patients. Here we report exome sequencing of 64 matched diagnosis/remission/relapses patients treated with historical RA/chemotherapy protocols. A first subgroup presents a high incidence of oncogenic mutations disrupting key epigenetic or transcriptional regulators (primarily WT1) or activating MAPK signaling at diagnosis. Relapses retain these cooperating oncogenes and exhibit additional oncogenic alterations and/or mutations impeding therapy response (RARA, NT5C2). The second group primarily exhibits FLT3 activation at diagnosis, which is lost upon relapse together with most other passenger mutations, implying that relapses derive from pre-leukemic PML/RARA-expressing cells that survived RA/chemotherapy. Accordingly, clonogenic activity of PML/RARA-immortalized progenitors ex vivo is only transiently affected by RA, but selectively abrogated by arsenic. Our studies stress the role of cooperating oncogenes in direct relapses and suggest that targeting pre-leukemic cells by arsenic contributes to its clinical efficacy.
| EGAS00001002893 | EGA
Project description:Loss of function mutations in the DNA methyltransferase DNMT3A are highly recurrent in acute myeloid leukemia (AML). DNMT3A and DNMT3B encode the two methyltransferases that are primarily responsible for the de novo methylation of specific DNA sequences during cellular differentiation. DNMT3A mutations are rarely found in AML patients with translocations that create oncogenic fusion genes (e.g. PML-RARA, RUNX1-RUNX1T1, CBFB-MYH11, and MLL-X). To begin to define the reasons why these mutations do not occur together, we used retroviral vectors to express PML-RARA, RUNX1-RUNX1T1, and MLL-AF9 in the bone marrow cells of wild type (WT) or Dnmt3a deficient mice; we also examined the hematopoietic phenotypes of Ctsg-PML-RARA animals (which express PML-RARA in early hematopoietic progenitors and myeloid precursors) with and without Dnmt3a. We demonstrated that the methyltransferase activity of Dnmt3a (but not Dnmt3b) is required for aberrant self-renewal ex vivo that is driven by PML-RARA (but not RUNX1-RUNX1T1 or MLL-AF9); furthermore, the PML-RARA-driven competitive transplantation advantage and leukemia generation both required Dnmt3a. Together, these findings demonstrate that PML-RARA is specifically dependent on Dnmt3a to initiate APL in mice, and may explain why loss-of-function DNMT3A mutations are not found in patients with acute promyelocytic leukemia.
2015-10-01 | GSE68844 | GEO
Project description:The PML-RARA fusion protein is the hallmark driver of Acute Promyelocytic Leukemia (APL) and disrupts retinoic acid signaling, leading to wide-scale gene expression changes and uncontrolled proliferation of myeloid precursor cells. While known to be recruited to binding sites across the genome, its impact on gene regulation and expression is under-explored. Using integrated multi-omics datasets, we characterize the influence of PML-RARA binding on gene expression and regulation in an inducible cell line model and APL patient ex vivo samples. We find that genes whose regulatory elements recruit PML-RARA are not uniformly transcriptionally repressed, as commonly suggested, but also may be upregulated or remain unchanged. We develop a novel, computational machine learning application to deconvolute the complex, local transcription factor binding site environment at PML-RARA bound positions to reveal distinct signatures that modulate how PML-RARA directs the transcriptional response.
2022-12-14 | GSE209833 | GEO
Project description:The PML-RARA fusion protein is the hallmark driver of Acute Promyelocytic Leukemia (APL) and disrupts retinoic acid signaling, leading to wide-scale gene expression changes and uncontrolled proliferation of myeloid precursor cells. While known to be recruited to binding sites across the genome, its impact on gene regulation and expression is under-explored. Using integrated multi-omics datasets, we characterize the influence of PML-RARA binding on gene expression and regulation in an inducible cell line model and APL patient ex vivo samples. We find that genes whose regulatory elements recruit PML-RARA are not uniformly transcriptionally repressed, as commonly suggested, but also may be upregulated or remain unchanged. We develop a novel, computational machine learning application to deconvolute the complex, local transcription factor binding site environment at PML-RARA bound positions to reveal distinct signatures that modulate how PML-RARA directs the transcriptional response.
2022-12-14 | GSE173754 | GEO
Project description:The PML-RARA fusion protein is the hallmark driver of Acute Promyelocytic Leukemia (APL) and disrupts retinoic acid signaling, leading to wide-scale gene expression changes and uncontrolled proliferation of myeloid precursor cells. While known to be recruited to binding sites across the genome, its impact on gene regulation and expression is under-explored. Using integrated multi-omics datasets, we characterize the influence of PML-RARA binding on gene expression and regulation in an inducible cell line model and APL patient ex vivo samples. We find that genes whose regulatory elements recruit PML-RARA are not uniformly transcriptionally repressed, as commonly suggested, but also may be upregulated or remain unchanged. We develop a novel, computational machine learning application to deconvolute the complex, local transcription factor binding site environment at PML-RARA bound positions to reveal distinct signatures that modulate how PML-RARA directs the transcriptional response.
2022-12-14 | GSE173753 | GEO
Project description:The PML-RARA fusion protein is the hallmark driver of Acute Promyelocytic Leukemia (APL) and disrupts retinoic acid signaling, leading to wide-scale gene expression changes and uncontrolled proliferation of myeloid precursor cells. While known to be recruited to binding sites across the genome, its impact on gene regulation and expression is under-explored. Using integrated multi-omics datasets, we characterize the influence of PML-RARA binding on gene expression and regulation in an inducible cell line model and APL patient ex vivo samples. We find that genes whose regulatory elements recruit PML-RARA are not uniformly transcriptionally repressed, as commonly suggested, but also may be upregulated or remain unchanged. We develop a novel, computational machine learning application to deconvolute the complex, local transcription factor binding site environment at PML-RARA bound positions to reveal distinct signatures that modulate how PML-RARA directs the transcriptional response.
2022-12-14 | GSE173751 | GEO
Project description:The PML-RARA fusion protein is the hallmark driver of Acute Promyelocytic Leukemia (APL) and disrupts retinoic acid signaling, leading to wide-scale gene expression changes and uncontrolled proliferation of myeloid precursor cells. While known to be recruited to binding sites across the genome, its impact on gene regulation and expression is under-explored. Using integrated multi-omics datasets, we characterize the influence of PML-RARA binding on gene expression and regulation in an inducible cell line model and APL patient ex vivo samples. We find that genes whose regulatory elements recruit PML-RARA are not uniformly transcriptionally repressed, as commonly suggested, but also may be upregulated or remain unchanged. We develop a novel, computational machine learning application to deconvolute the complex, local transcription factor binding site environment at PML-RARA bound positions to reveal distinct signatures that modulate how PML-RARA directs the transcriptional response.
2022-12-14 | GSE173752 | GEO
Project description:The aim of this study is to identify microRNAs (miRNAs) transcriptionnally regulated by retinoic acid (RA). For that purpose we have used the RA-based treatment of the Acute Promyelocytic Leukemia (APL) as a model. This malignancy is characterised by a differentiation arrest of granulopoiesis at the promyelocytic stage. APL is molecularly associated with reciprocal translocations that always involve the retinoic acid receptor a (RARa). In the vast majority of APL cases, a t(15;17) chromosomal translocation fuses the genes encoding the promyelocytic leukemia protein PML and RARa. The resulting PML-RARa is a transcriptional repressor that impedes the expression of RA-regulated genes notably through an aberrant recruitment of transcriptional repressors and histone deacetylases. Consequently, these genes become insensitive to physiological doses (nanoM) of all-trans-retinoic acid (ATRA) but pharmacological doses (microM), overcome the PML-RARa-mediated repression and restore normal transcription and granulocytic differentiation. The restorative effects of RA can be reproduced in vitro in the NB4 cells, which were derived from an APL patient. These cells provide an excellent model to study the transcriptional deregulations that arise in APL and the molecular effects of the anti-cancerous RA-based treatment. We also used in this study the RA-resistant cells, namely NB4-LR1 and NB4-LR2 cells. The NB4-LR1 cells do transcriptionally respond to ATRA but do not maturate. In contrast, the NB4-LR2 cells show a clear defect in RA signaling, as they harbor a truncated form of PML-RAR protein that is not sensitive to pharmacological doses of RA. First, we plan to characterize miRNAs-repressed by PML-RAR. We reasoned that if some miRNAs are repressed by this protein, then pharmacological doses of RA should abolish this repression and lead to an increase in the level of expression of the corresponding miRNAs. NB4, NB4-LR1 and NB4-LR2 cells will thus be treated for 16h with ATRA (1 microM), and miRNAs profiles will be compared. We anticipate that, the expression of a potential miRNA-repressed by PML-RAR should be up-regulated by ATRA in both NB4 and NB4-LR1 cells but remain unchanged in NB4-LR2 cells. This expression pattern should in fact be similar to those observed for known RA-regulated genes, such as RARb, a well characterized target of the RARa and PML-RAR proteins. Importantly, this experimental procedure was already validated with the identification of a miRNA repressed by PML-RAR (patent Lecellier et al. #WO 2006/048553). MiRNAs candidates obtained will then be validated by chromatin immunoprecipitation using anti-RARa and anti-PML antibodies, followed by luciferase assays in presence or absence of ATRA. Keywords: retinoic acid-mediated gene regulation To characterize miRNAs regulated by PML-RAR.
2008-11-17 | E-GEOD-11379 | biostudies-arrayexpress
Project description:The PML-RARA fusion protein is the hallmark driver of Acute Promyelocytic Leukemia (APL) and disrupts retinoic acid signaling, leading to wide-scale gene expression changes and uncontrolled proliferation of myeloid precursor cells. While known to be recruited to binding sites across the genome, its impact on gene regulation and expression is under-explored. Using integrated multi-omics datasets, we characterize the influence of PML-RARA binding on gene expression and regulation in an inducible cell line model and APL patient ex vivo samples. We find that genes whose regulatory elements recruit PML-RARA are not uniformly transcriptionally repressed, as commonly suggested, but also may be upregulated or remain unchanged. We apply a novel computational deep learning strategy to deconvolute the complex, local transcription factor binding site environment at PML-RARA bound positions to reveal distinct signatures that modulate how PML-RARA directs the transcriptional response.
2022-12-14 | GSE215101 | GEO