Browse
Submit Data
Databases
API
Help

Dataset Information

8 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A transcriptomic continuum of differentiation arrest identifies myeloid interface acute leukemias with poor prognosis.

ABSTRACT: Classification of acute lymphoblastic and myeloid leukemias (ALL and AML) remains heavily based on phenotypic resemblance to normal hematopoietic precursors. This framework can provide diagnostic challenges for immunophenotypically heterogeneous immature leukemias, and ignores recent advances in understanding of developmental multipotency of diverse normal hematopoietic progenitor populations that are identified by transcriptional signatures. We performed transcriptional analyses of a large series of acute myeloid and lymphoid leukemias and detected significant overlap in gene expression between cases in different diagnostic categories. Bioinformatic classification of leukemias along a continuum of hematopoietic differentiation identified leukemias at the myeloid/T-lymphoid interface, which shared gene expression programs with a series of multi or oligopotent hematopoietic progenitor populations, including the most immature CD34+CD1a-CD7- subset of early thymic precursors. Within these interface acute leukemias (IALs), transcriptional resemblance to early lymphoid progenitor populations and biphenotypic leukemias was more evident in cases originally diagnosed as AML, rather than T-ALL. Further prognostic analyses revealed that expression of IAL transcriptional programs significantly correlated with poor outcome in independent AML patient cohorts. Our results suggest that traditional binary approaches to acute leukemia categorization are reductive, and that identification of IALs could allow better treatment allocation and evaluation of therapeutic options.

SUBMITTER: Bond J

PROVIDER: S-EPMC7932917 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

A transcriptomic continuum of differentiation arrest in acute leukemias

Project description:This SuperSeries is composed of the SubSeries listed below.

2019-12-09 | GSE131207 | GEO

A transcriptomic continuum of differentiation arrest in acute leukemias

Project description:A transcriptomic continuum of differentiation arrest in acute leukemias

| PRJNA542908 | ENA

AKT/FOXO signaling enforces reversible differentiation blockade in myeloid leukemias.

Project description:AKT activation is associated with many malignancies, where AKT acts, in part, by inhibiting FOXO tumor suppressors. We show a converse role for AKT/FOXOs in acute myeloid leukemia (AML). Rather than decreased FOXO activity, we observed that FOXOs are active in ?40% of AML patient samples regardless of genetic subtype. We also observe this activity in human MLL-AF9 leukemia allele-induced AML in mice, where either activation of Akt or compound deletion of FoxO1/3/4 reduced leukemic cell growth, with the latter markedly diminishing leukemia-initiating cell (LIC) function in vivo and improving animal survival. FOXO inhibition resulted in myeloid maturation and subsequent AML cell death. FOXO activation inversely correlated with JNK/c-JUN signaling, and leukemic cells resistant to FOXO inhibition responded to JNK inhibition. These data reveal a molecular role for AKT/FOXO and JNK/c-JUN in maintaining a differentiation blockade that can be targeted to inhibit leukemias with a range of genetic lesions.

| S-EPMC3826540 | biostudies-literature

ARHGEF3 controls HDACi-induced differentiation via RhoA-dependent pathways in acute myeloid leukemias.

Project description:Altered expression and activity of histone deacetylases (HDACs) have been correlated with tumorigenesis. Inhibitors of HDACs (HDACi) induce acetylation of histone and non-histone proteins affecting gene expression, cell cycle progression, cell migration, terminal differentiation and cell death. Here, we analyzed the regulation of ARHGEF3, a RhoA-specific guanine nucleotide exchange factor, by the HDACi MS275 (entinostat). MS275 is a well-known benzamide-based HDACi, which induces differentiation of the monoblastic-like human histiocytic lymphoma cell line U937 to monocytes/macrophages. Incubation of U937 cells with MS275 resulted in an up regulation of ARHGEF3, followed by a significant enhancement of the marker of macrophage differentiation CD68. ARHGEF3 protein is primarily nuclear, but MS275 treatment rapidly induced its translocation into the cytoplasm. ARHGEF3 cytoplasmic localization is associated with activation of the RhoA/Rho-associated Kinase (ROCK) pathway. In addition to cytoskeletal rearrangements orchestrated by RhoA, we showed that ARHGEF3/RhoA-dependent signals involve activation of SAPK/JNK and then Elk1 transcription factor. Importantly, MS275-induced CD68 expression was blocked by exposure of U937 cells to exoenzyme C3 transferase and Y27632, inhibitors of Rho and ROCK respectively. Moreover, ARHGEF3 silencing prevented RhoA activation leading to a reduction in SAPK/JNK phosphorylation, Elk1 activation and CD68 expression, suggesting a crucial role for ARHGEF3 in myeloid differentiation. Taken together, our results demonstrate that ARHGEF3 modulates acute myeloid leukemia differentiation through activation of RhoA and pathways directly controlled by small GTPase family proteins. The finding that GEF protein modulation by HDAC inhibition impacts on cell differentiation may be important for understanding the antitumor mechanism(s) by which HDACi treatment stimulates differentiation in cancer.

| S-EPMC4622697 | biostudies-literature

Poor Prognosis in Acute Myeloid Leukemia Patients with Monosomal Karyotypes.

Project description:This study aimed to investigate the clinical characteristics and prognostic significance of monosomal karyotypes (MKs) in patients with acute myeloid leukemia (AML).We retrospectively analyzed the clinical data for 498 patients with AML, of whom 233 (46.8%) had an abnormal karyotype, including 42 with MKs (8.4%) and 70 with a complex karyotype (CK) (14.1%).Patients with MKs were older (median age 62.5 vs. 52 years, p=0.003) and had lower median hemoglobin levels (62.5 vs. 77 g/L, p=0.009) and lower white blood cell counts (7.0×109/L vs. 11.7×109/L, p=0.008). Univariate analysis showed that patients with MKs or CKs had shorter overall survival than patients without these karyotypes (median survival time 7.3 vs. 26.3 months for MK, p<0.001, and 14.8 vs. 26.3 months for CK, p<0.001). In multivariable analysis for overall survival, MK and National Comprehensive Cancer Network prognostic group were the only significant factors.MK is an independent risk factor for poor prognosis in AML patients.

| S-EPMC5440863 | biostudies-other

Integrative Genomic Analysis of Pediatric Myeloid-Related Acute Leukemias Identifies Novel Subtypes and Prognostic Indicators

Project description:Integrating somatic mutation analysis and gene expression profiling distinguishes pediatric AML subtypes with differential prognoses and clinical risks. Genomic characterization of pediatric patients with acute myeloid leukemia (AML) has led to the discovery of somatic mutations with prognostic implications. Although gene-expression profiling can differentiate subsets of pediatric AML, its clinical utility in risk stratification remains limited. Here, we evaluate gene expression, pathogenic somatic mutations, and outcome in a cohort of 435 pediatric patients with a spectrum of pediatric myeloid-related acute leukemias for biological subtype discovery. This analysis revealed 63 patients with varying immunophenotypes that span a T-lineage and myeloid continuum designated as acute myeloid/T-lymphoblastic leukemia (AMTL). Within AMTL, two patient subgroups distinguished by FLT3-ITD and PRC2 mutations have different outcomes, demonstrating the impact of mutational composition on survival. Across the cohort, variability in outcomes of patients within isomutational subsets is influenced by transcriptional identity and the presence of a stem cell–like gene-expression signature. Integration of gene expression and somatic mutations leads to improved risk stratification. Significance: Immunophenotype and somatic mutations play a significant role in treatment approach and risk stratification of acute leukemia. We conducted an integrated genomic analysis of pediatric myeloid malignancies and found that a combination of genetic and transcriptional readouts was superior to immunophenotype and genomic mutations in identifying biological subtypes and predicting outcomes. This article is highlighted in the In This Issue feature, p. 549

| S-EPMC8580615 | biostudies-literature

Deregulated KLF4 Expression in Myeloid Leukemias Alters Cell Proliferation and Differentiation through MicroRNA and Gene Targets.

Project description:Acute myeloid leukemia (AML) is characterized by increased proliferation and blocked differentiation of hematopoietic progenitors mediated, in part, by altered myeloid transcription factor expression. Decreased Krüppel-like factor 4 (KLF4) expression has been observed in AML, but how decreased KLF4 contributes to AML pathogenesis is largely unknown. We demonstrate decreased KLF4 expression in AML patient samples with various cytogenetic aberrations, confirm that KLF4 overexpression promotes myeloid differentiation and inhibits cell proliferation in AML cell lines, and identify new targets of KLF4. We have demonstrated that microRNA 150 (miR-150) expression is decreased in AML and that reintroducing miR-150 expression induces myeloid differentiation and inhibits proliferation of AML cells. We show that KLF family DNA binding sites are necessary for miR-150 promoter activity and that KLF2 or KLF4 overexpression induces miR-150 expression. miR-150 silencing, alone or in combination with silencing of CDKN1A, a well-described KLF4 target, did not fully reverse KLF4-mediated effects. Gene expression profiling and validation identified putative KLF4-regulated genes, including decreased MYC and downstream MYC-regulated gene expression in KLF4-overexpressing cells. Our findings indicate that decreased KLF4 expression mediates antileukemic effects through regulation of gene and microRNA networks, containing miR-150, CDKN1A, and MYC, and provide mechanistic support for therapeutic strategies increasing KLF4 expression.

| S-EPMC4751692 | biostudies-literature

Exome Sequencing of Poor Prognosis Acute Myeloid Leukaemia

Project description:We plan to sequence the exomes of 4 AML cases (tumour and germline) in an effort to discover new mutations in this disease that could improve our understanding of leukaemogenesis and guide the development of new targeted therapies. The Sanger Institute will sequence the exomes of 4 Acute Myeloid Leukaemia cases including tumour and germline DNA so that somatically-acquired, AML-specific mutations can be accurately designated.

| EGAS00001000146 | EGA

C/EBPγ deregulation results in differentiation arrest in acute myeloid leukemia.

Project description:C/EBPs are a family of transcription factors that regulate growth control and differentiation of various tissues. We found that C/EBPγ is highly upregulated in a subset of acute myeloid leukemia (AML) samples characterized by C/EBPα hypermethylation/silencing. Similarly, C/EBPγ was upregulated in murine hematopoietic stem/progenitor cells lacking C/EBPα, as C/EBPα mediates C/EBPγ suppression. Studies in myeloid cells demonstrated that CEBPG overexpression blocked neutrophilic differentiation. Further, downregulation of Cebpg in murine Cebpa-deficient stem/progenitor cells or in human CEBPA-silenced AML samples restored granulocytic differentiation. In addition, treatment of these leukemias with demethylating agents restored the C/EBPα-C/EBPγ balance and upregulated the expression of myeloid differentiation markers. Our results indicate that C/EBPγ mediates the myeloid differentiation arrest induced by C/EBPα deficiency and that targeting the C/EBPα-C/EBPγ axis rescues neutrophilic differentiation in this unique subset of AMLs.

| S-EPMC3533560 | biostudies-literature

Up-regulation of DDIT4 predicts poor prognosis in acute myeloid leukaemia.

Project description:The mammalian target of rapamycin (mTOR) inhibitor, DNA damage inducible transcript 4 (DDIT4), has inducible expression in response to various cellular stresses. In multiple malignancies, studies have shown that DDIT4 participates in tumorigenesis and impacts patient survival. We aimed to study the prognostic value of DDIT4 in acute myeloid leukaemia (AML), which is currently unclear. Firstly, The Cancer Genome Atlas was screened for AML patients with complete clinical characteristics and DDIT4 expression data. A total of 155 patients were included and stratified according to the treatment modality and the median DDIT4 expression levels. High DDIT4 expressers had shorter overall survival (OS) and event-free survival (EFS) than the low expressers among the chemotherapy-only group (all P < .001); EFS and OS were similar in the high and low DDIT4 expressers of the allogeneic haematopoietic stem cell transplantation (allo-HSCT) group. Furthermore, in the DDIT4high group, patients treated with allo-HSCT had longer EFS and OS than those who received chemotherapy alone (all P < .01). In the DDIT4low group, OS and EFS were similar in different treatment groups. Secondly, we analysed two other cytogenetically normal AML (CN-AML) cohorts derived from the Gene Expression Omnibus database, which confirmed that high DDIT4 expression was associated with poorer survival. Gene Ontology (GO) enrichment analysis showed that the genes related to DDIT4 expression were mainly concentrated in the acute and chronic myeloid leukaemia signalling pathways. Collectively, our study indicates that high DDIT4 expression may serve as a poor prognostic factor for AML, but its prognostic effects could be outweighed by allo-HSCT.

| S-EPMC6933361 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data