Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Transcription profiling by array of bone marrow and peripheral blood samples from patients with cytogenetically normal acute myeloid leukemia to study gene expression profiles associated with different levels of miR-3151 expression

ABSTRACT: Recently, deep sequencing of melanoma and pediatric acute lymphoblastic leukemia samples identified a new microRNA - miR-3151 - embedded in intron 1 of the BAALC gene. MiR genes are located throughout the genome, but about one-third of mammalian miRs reside within introns of host genes. Some of these intronic miRs have been found to act in functional synergism with their host genes. These findings led us to hypothesize that miR-3151 could be overexpressed in patients with elevated BAALC levels and thus might contribute to the adverse prognostic impact of its host gene, either acting in concert with BAALC or perhaps even being the element predominantly responsible for the adverse outcome observed in BAALC overexpressing AML patients.Thus, we have measured miR-3151 and BAALC expression in a cohort of molecularly well characterized de novo CN-AML patients to assess the impact of miR-3151 expression alone and in combination with its host BAALC on outcome. microRNA expression profiles associated with miR-3151 expression in older patients with cytogenetically normal acute myeloid leukemia were derived using microarrays. The corresponding microRNA expression data can be found under accession number E-MTAB-1074.

ORGANISM(S): Homo sapiens

SUBMITTER: Marcucci Guido

PROVIDER: S-ECPF-MTAB-1075 | biostudies-other |

REPOSITORIES: biostudies-other

ACCESS DATA

Json Xml

Similar Datasets

MicroRNA profiling by array of bone marrow from patients with cytogenetically normal acute myeloid leukemia to study microRNA expression profiles associated with different levels of miR-3151 expression

Project description:Recently, deep sequencing of melanoma and pediatric acute lymphoblastic leukemia samples identified a new microRNA - miR-3151 - embedded in intron 1 of the BAALC gene. MiR genes are located throughout the genome, but about one-third of mammalian miRs reside within introns of host genes. Some of these intronic miRs have been found to act in functional synergism with their host genes. These findings led us to hypothesize that miR-3151 could be overexpressed in patients with elevated BAALC levels and thus might contribute to the adverse prognostic impact of its host gene, either acting in concert with BAALC or perhaps even being the element predominantly responsible for the adverse outcome observed in BAALC overexpressing AML patients.Thus, we have measured miR-151 and BAALC expression in a cohort of molecularly well characterized de novo CN-AML patients to assess the impact of miR-3151 expression alone and in combination with its host BAALC on outcome. microRNA expression profiles associated with miR-3151 expression in older patients with cytogenetically normal acute myeloid leukemia were derived using microarrays. The corresponding affymetrix data can be found under accession number E-MTAB-1075.

| S-ECPF-MTAB-1074 | biostudies-other

Comparison of gene-expression profiles in parallel bone marrow and peripheral blood samples in acute myeloid leukaemia by real-time polymerase chain reaction.

Project description:BackgroundGene signatures (Indicator genes) in bone marrow that provide more precise prognostication in haematological malignancy have been identified by microarray expression studies. It would be beneficial to measure these diagnostic signatures in peripheral blood.AimsTo determine the degree of correspondence of gene expression for a set of Indicator genes between bone marrow and peripheral blood in acute myeloid leukaemia (AML).MethodsParallel bone marrow aspirate and peripheral blood samples were obtained from 19 patients diagnosed with AML and mononuclear cells isolated from both sample types. mRNA was globally amplified by polyadenylated real-time polymerase chain reaction (polyA RT-PCR); the expression of 15 AML Indicator genes, identified from previous microarray studies, was measured by RT-PCR. All values were normalised to the mean expression of three housekeeping genes (IF2-beta, GAP and RbS9) and were statistically compared using SPSS software.ResultsNo significant difference in expression between bone marrow and peripheral blood was observed for 10 of the genes (leptin receptor, CD33, adipsin, proteoglycan 1, MB-1, cyclin D3, hSNF2b, proteasome iota, HkrT-1 and E2A), indicating its possible use in monitoring disease activity in peripheral blood samples, whereas c-myb, HOXA9, LYN, cystatin c and LTC4s showed significantly different expression between bone marrow and peripheral blood samples.ConclusionThese results indicate a possible use for the method in monitoring AML in peripheral blood by RT-PCR measurement of Indicator genes. In addition, the initial use of polyA PCR facilitates translation to very small clinical samples, including fractionated cell populations, of particular importance for monitoring haematological malignancy.

| S-EPMC1861748 | biostudies-literature

Development of gene expression-based risk score in cytogenetically normal acute myeloid leukemia patients.

Project description:Patients with normal karyotype represent the single largest cytogenetic group of acute myeloid leukemia (AML), with highly heterogeneous clinical and molecular characteristics. In this study, we sought to determine new prognostic biomarkers in cytogenetically normal (CN)-AML patients. A gene expression (GE)-based risk score was built, summing up the prognostic value of 22 genes whose expression is associated with a bad prognosis in a training cohort of 163 patients. GE-based risk score allowed identifying a high-risk group of patients (53.4%) in two independent cohorts of CN-AML patients. GE-based risk score and EVI1 gene expression remained independent prognostic factors using multivariate Cox analyses. Combining GE-based risk score with EVI1 gene expression allowed the identification of three clinically different groups of patients in two independent cohorts of CN-AML patients. Thus, GE-based risk score is powerful to predict clinical outcome for CN-AML patients and may provide potential therapeutic advances.

| S-EPMC3478459 | biostudies-literature

Prognostic Prediction of Cytogenetically Normal Acute Myeloid Leukemia Based on a Gene Expression Model.

Project description:Acute myeloid leukemia (AML) refers to a heterogeneous group of hematopoietic malignancies. The well-known European Leukemia Network (ELN) stratifies AML patients into three risk groups, based primarily on the detection of cytogenetic abnormalities. However, the prognosis of cytogenetically normal AML (CN-AML), which is the largest AML subset, can be hard to define. Moreover, the clinical outcomes associated with this subgroup are diverse. In this study, using transcriptome profiles collected from CN-AML patients in the BeatAML cohort, we constructed a robust prognostic Cox model named NEST (Nine-gEne SignaTure). The validity of NEST was confirmed in four external independent cohorts. Moreover, the risk score predicted by the NEST model remained an independent prognostic factor in multivariate analyses. Further analysis revealed that the NEST model was suitable for bone marrow mononuclear cell (BMMC) samples but not peripheral blood mononuclear cell (PBMC) samples, which indirectly indicated subtle differences between BMMCs and PBMCs. Our data demonstrated the robustness and accuracy of the NEST model and implied the importance of the immune dysfunction in the leukemogenesis that occurs in CN-AML, which shed new light on the further exploration of molecular mechanisms and treatment guidance for CN-AML.

| S-EPMC8190396 | biostudies-literature

Gene expression signature predicts relapse in adult patients with cytogenetically normal acute myeloid leukemia.

Project description:Although ∼80% of adult patients with cytogenetically normal acute myeloid leukemia (CN-AML) achieve a complete remission (CR), more than half of them relapse. Better identification of patients who are likely to relapse can help to inform clinical decisions. We performed RNA sequencing on pretreatment samples from 268 adults with de novo CN-AML who were younger than 60 years of age and achieved a CR after induction treatment with standard "7+3" chemotherapy. After filtering for genes whose expressions were associated with gene mutations known to impact outcome (ie, CEBPA, NPM1, and FLT3-internal tandem duplication [FLT3-ITD]), we identified a 10-gene signature that was strongly predictive of patient relapse (area under the receiver operating characteristics curve [AUC], 0.81). The signature consisted of 7 coding genes (GAS6, PSD3, PLCB4, DEXI, JMY, NRP1, C10orf55) and 3 long noncoding RNAs. In multivariable analysis, the 10-gene signature was strongly associated with relapse (P < .001), after adjustment for the FLT3-ITD, CEBPA, and NPM1 mutational status. Validation of the expression signature in an independent patient set from The Cancer Genome Atlas showed the signature's strong predictive value, with AUC = 0.78. Implementation of the 10-gene signature into clinical prognostic stratification could be useful for identifying patients who are likely to relapse.

| S-EPMC7948288 | biostudies-literature

Molecular prognostic factors in cytogenetically normal acute myeloid leukemia.

Project description:Chromosomal abnormalities are detected in 50-60% of patients with acute myeloid leukemia (AML) and are important predictors of prognosis and risk of relapse. The remaining patients, those with cytogenetically normal AML, are a seemingly homogeneous group that in fact consists of subsets of patients with distinct clinical outcomes. This heterogeneity is likely related to acquired gene mutations, as well as altered miRNA and gene-expression profiles, which occur within the group. The identification of recurrent molecular abnormalities has improved prognostication and provided insight into mechanisms of leukemogenesis for patients with cytogenetically normal AML, as well as led to the discovery of novel therapeutic targets. As the number of mutations continues to expand, bioinformatic algorithms that allow for integration of multiple markers will be necessary to provide optimal care for patients with this disease.

| S-EPMC3582378 | biostudies-literature

Impact of Bone Marrow miR-21 Expression on Acute Myeloid Leukemia T Lymphocyte Fragility and Dysfunction.

Project description:BackgroundAcute myeloid leukemia (AML) is a hematopoietic malignancy in which antitumor immunity is impaired. The therapeutic management of AML requires understanding the mechanisms involved in the fragility and immune dysfunction of AML T lymphocytes.MethodsIn this study, T lymphocytes from healthy donors (HD) and AML patients were used. Extracellular vesicles (EVs) from leukemic cells were screened for their microRNA content and impact on T lymphocytes. Flow cytometry, transcriptomic as well as lentiviral transduction techniques were used to carry out the research.ResultsWe observed increased cell death of T lymphocytes from AML patients. EVs from leukemia myeloid cell lines harbored several miRNAs, including miR-21, and were able to induce T lymphocyte death. Compared to that in HD, miR-21 was overexpressed in both the bone marrow fluid and infiltrating T lymphocytes of AML patients. MiR-21 induces T lymphocyte cell death by upregulating proapoptotic gene expression. It also increases the immunosuppressive profile of T lymphocytes by upregulating the IL13, IL4, IL10, and FoxP3 genes.ConclusionsOur results demonstrate that miR-21 plays a significant role in AML T lymphocyte dysfunction and apoptosis. Targeting miR-21 may be a novel approach to restore the efficacy of the immune response against AML.

| S-EPMC7563595 | biostudies-literature

An 86-probe-set gene-expression signature predicts survival in cytogenetically normal acute myeloid leukemia.

Project description:Patients with cytogenetically normal acute myeloid leukemia (CN-AML) show heterogeneous treatment outcomes. We used gene-expression profiling to develop a gene signature that predicts overall survival (OS) in CN-AML. Based on data from 163 patients treated in the German AMLCG 1999 trial and analyzed on oligonucleotide microarrays, we used supervised principal component analysis to identify 86 probe sets (representing 66 different genes), which correlated with OS, and defined a prognostic score based on this signature. When applied to an independent cohort of 79 CN-AML patients, this continuous score remained a significant predictor for OS (hazard ratio [HR], 1.85; P = .002), event-free survival (HR = 1.73; P = .001), and relapse-free survival (HR = 1.76; P = .025). It kept its prognostic value in multivariate analyses adjusting for age, FLT3 ITD, and NPM1 status. In a validation cohort of 64 CN-AML patients treated on CALGB study 9621, the score also predicted OS (HR = 4.11; P < .001), event-free survival (HR = 2.90; P < .001), and relapse-free survival (HR = 3.14, P < .001) and retained its significance in a multivariate model for OS. In summary, we present a novel gene-expression signature that offers additional prognostic information for patients with CN-AML.

| S-EPMC2954679 | biostudies-literature

High expression of RUNX1 is associated with poorer outcomes in cytogenetically normal acute myeloid leukemia.

Project description:Depending on its expression level, RUNX1 can act as a tumor promoter or suppressor in hematological malignancies. The clinical impact of RUNX1 expression in cytogenetically normal acute myeloid leukemia (CN-AML) remained unknown, however. We evaluated the prognostic significance of RUNX1 expression using several public microarray datasets. In the testing group (n = 157), high RUNX1 expression (RUNX1high) was associated with poorer overall survival (OS; P = 0.0025) and event-free survival (EFS; P = 0.0025) than low RUNX1 expression (RUNX1low). In addition, the prognostic significance of RUNX1 was confirmed using European Leukemia Net (ELN) genetic categories and multivariable analysis, which was further validated using a second independent CN-AML cohort (n = 162, OS; P = 0.03953). To better understand the mechanisms of RUNX1, we investigated genome-wide gene/microRNAs expression signatures and cell signaling pathways associated with RUNX1 expression status. Several known oncogenes/oncogenic microRNAs and cell signaling pathways were all up-regulated, while some anti-oncogenes and molecules of immune activation were down-regulated in RUNX1high CN-AML patients. These findings suggest RUNX1high is a prognostic biomarker of unfavorable outcome in CN-AML, which is supported by the distinctive gene/microRNA signatures and cell signaling pathways.

| S-EPMC4941280 | biostudies-literature

Prognostically important molecular markers in cytogenetically normal acute myeloid leukemia.

Project description:Cytogenetically normal acute myeloid leukemia (CN-AML) is a heterogeneous disease with variable clinical outcomes. Emerging data has identified molecular markers that provide additional prognostic information to better classify these patients into those with a more favorable prognosis and those with an unfavorable prognosis who may require more aggressive or investigational therapies. Markers such as mutations in nucleophosmin 1 gene and CCAAT/enhancer binding protein alpha gene have been associated with a more favorable prognosis in CN-AML. In contrast, FMS-related tyrosine kinase 3 mutations, partial tandem duplication of mixed-lineage leukemia gene and overexpression of brain and acute leukemia, cytoplasmic gene are associated with inferior clinical outcomes. In this article, the authors discuss the classical clinical features of AML and the importance of cytogenetics that predict prognosis in AML. They review the best-described molecular markers in CN-AML and their significance to clinical decision making in CN-AML.

| S-EPMC4234091 | 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