Dataset Information

ESRRB regulates glucocorticoid gene expression in mice and patients with acute lymphoblastic leukemia

ABSTRACT: Synthetic glucocorticoids (GCs), such as dexamethasone and prednisone, remain key components of therapy for patients with lymphoid malignancies. For pediatric patients with acute lymphoblastic leukemia (ALL), response to GCs remains the most reliable prognostic indicator; failure to respond to GC correlates with poor event-free survival. To uncover GC resistance mechanisms, we performed a genome-wide, survival-based short hairpin RNA screen and identified the orphan nuclear receptor estrogen-related receptor-? (ESRRB) as a critical transcription factor that cooperates with the GC receptor (GR) to mediate the GC gene expression signature in mouse and human ALL cells. Esrrb knockdown interfered with the expression of genes that were induced and repressed by GR and resulted in GC resistance in vitro and in vivo. Dexamethasone treatment stimulated ESRRB binding to estrogen-related receptor elements (ERREs) in canonical GC-regulated genes, and H3K27Ac Hi-chromatin immunoprecipitation revealed increased interactions between GR- and ERRE-containing regulatory regions in dexamethasone-treated human T-ALL cells. Furthermore, ESRRB agonists enhanced GC target gene expression and synergized with dexamethasone to induce leukemic cell death, indicating that ESRRB agonists may overcome GC resistance in ALL, and potentially, in other lymphoid malignancies.

ORGANISM(S): Mus musculus

PROVIDER: GSE115363 | GEO | 2020/07/20

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Glucocorticoids (GCs) are commonly used to treat patients suffering from lymphoid malignancies i.e. leukemia and multiple myeloma. Although GCs are known to be strong inducers of apoptosis in lymphoid cells, the molecular determinants of GC therapy resistance are poorly understood. Although GC treatment triggers important changes in gene expression, few studies have addressed the regulatory role of small regulatory microRNAs (miRNAs) in GC therapy response. Only recently, aberrant microRNA expression has been linked to the development of haematological malignancies and microRNAs have become master regulators of drug resistance. We identified GC inducible mRNA and microRNA transcription profiles in GC sensitive MM1S as compared to GC resistant MM1R cells. Transcriptome analysis revealed that GCs regulate multiple genes involved in cell cycle control, cell organization and cell death in MM1S, which remain unaffected in MM1R cells. Correspondingly, GCs selectively trigger cell death in MM1S but not in MM1R. Out of 32 microRNAs responsive to GC in MM1S cells but not in MM1R cells, mir-150 was identified as the most persistent GC responsive microRNA. Furthermore, Ingenuity Pathways Analysis (IPA) revealed that ectopic transfection of a synthetic mir-150 mimics GC therapy response in MM1S cells, associated with selective changes in mRNA levels of typical GR transactivated and transrepressed target genes. Although mir-150 largely mirrors GC responsive changes in gene expression of the transcription factor Myb, GR chaperone FKBP5, cell cycle modulator proteins (IL23A, SKP2, CDKN1A), chemokine signaling proteins (CXCR4, CX3CR1, CCL3) and mTOR/UPR stress related proteins (DDIT4, TXNIP), we also observed mir-150 selective effects on transcription factors (NR3C2 (MR), Myb, Fos, Jun, C/EBP-beta, IRF4, NFE2L1, ATF3, ATF4,), chaperone molecules HSPA8, HSP90AB1), the sodium channel SCNN1G and UPR stress proteins (TRIB3, DDIT3). Remarkably, mir-150 overexpression was not able to overcome GC therapy resistance, since we could not detect GC like effects of mir-150 in GR (NR3C1) deficient MM1R cells. Altogether GC-inducible mir-150 adds a novel complex layer of regulation for fine tuning GC specific therapeutic responses in multiple myeloma.

Dataset Information

ESRRB regulates glucocorticoid gene expression in mice and patients with acute lymphoblastic leukemia

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets