Dataset Information

MicroRNAs distinguish cytogenetic subgroups in pediatric AML and contribute to complex regulatory networks in AML-relevant pathways.

ABSTRACT:

Background

The role of microRNAs (miRNAs), important post-transcriptional regulators, in the pathogenesis of acute myeloid leukemia (AML) is just emerging and has been mainly studied in adults. First studies in children investigate single selected miRNAs, however, a comprehensive overview of miRNA expression and function in children and young adults is missing so far.

Methodology/principal findings

We here globally identified differentially expressed miRNAs between AML subtypes in a survey of 102 children and adolescent. Pediatric samples with core-binding factor AML and promyelocytic leukemia could be distinguished from each other and from MLL-rearranged AML subtypes by differentially expressed miRNAs including miR-126, -146a, -181a/b, -100, and miR-125b. Subsequently, we established a newly devised immunoprecipitation assay followed by rapid microarray detection for the isolation of Argonaute proteins, the hallmark of miRNA targeting complexes, from cell line models resembling core-binding factor and promyelocytic leukemia. Applying this method, we were able to identify Ago-associated miRNAs and their targeted mRNAs.

Conclusions/significance

miRNAs as well as their mRNA-targets showed binding preferences for the different Argonaute proteins in a cell context-dependent manner. Bioinformatically-derived pathway analysis suggested a concerted action of all four Argonaute complexes in the regulation of AML-relevant pathways. For the first time, to our knowledge, a complete AML data set resulting from carefully devised biochemical isolation experiments and analysis of Ago-associated miRNAs and their target-mRNAs is now available.

SUBMITTER: Daschkey S

PROVIDER: S-EPMC3572007 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Publications

MicroRNAs distinguish cytogenetic subgroups in pediatric AML and contribute to complex regulatory networks in AML-relevant pathways.

Daschkey Svenja S Röttgers Silja S Giri Anamika A Bradtke Jutta J Teigler-Schlegel Andrea A Meister Gunter G Borkhardt Arndt A Landgraf Pablo P

PloS one 20130213 2

<h4>Background</h4>The role of microRNAs (miRNAs), important post-transcriptional regulators, in the pathogenesis of acute myeloid leukemia (AML) is just emerging and has been mainly studied in adults. First studies in children investigate single selected miRNAs, however, a comprehensive overview of miRNA expression and function in children and young adults is missing so far.<h4>Methodology/principal findings</h4>We here globally identified differentially expressed miRNAs between AML subtypes in ...[more]

PMID: 23418555

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Project description:microRNAs, important regulators of cell proliferation and apoptosis, have been shown to be involved in the pathogenesis of acute myeloid leukemia in adulthood AML. However, comprehensive studies in AML of children and adolescents are missing so far. We investigated the miRNA expression profiles of different AML subtypes from 102 pediatric patients in comparison to CD34+ cells from healthy donors and adult AML patients, in order to identify differentially expressed miRNAs. Pediatric samples with core factor binding acute myeloid leukemia and promyelocytic leukemia could be distinguished from each other and MLL rearranged AML subtypes by 9 and 18 miRNAs, respectively. miR-126, -146a, -181a/b, -100, and miR-125b were identified as highest differentially expressed with marked difference of expression between pediatric and adulthood samples of the same cytogenetic subgroup. We next isolated the miRNA targeting complex from t(8;21) and t(15;17) cell line models and comprehensively identified bound miRNAs and targeted mRNAs by a newly devised immunoprecipitation assay followed by rapid microarray detection. Our findings indicate separate binding preferences for the four human Argonaute proteins. Subsequent bioinformatic analysis revealed a concerted action of different Ago proteins in the regulation of AML-relevant pathways, providing an experimental based database of miRNA-mRNA target interaction in Argonaute proteins. Ago-associated microRNAs: Co-immunoprecipitation in the acute myeloid leukemia cell line models, KASUMI-1 and NB4, of the four human Argonaute complexes using monoclonal antibodies and stringent washing conditions. We performed photo-activated UV cross-linking using 4M-bM-^@M-^Y-thioruidine before cell lysis. Unspecific binding to the bead matrix and to the Fc part of the monoclonal rat antibody were recorded and corrected by empty bead controls and an antibody isotype control. Argonaute-associated miRNAs/mRNAs and unspecific bound miRNAs/mRNAs of the isotype control were identified by microarray hybridization. These experiments were performed in triplicates. Ago-associated mRNAs: Co-immunoprecipitation in the acute myeloid leukemia cell line models, KASUMI-1 and NB4, of the four human Argonaute complexes using monoclonal antibodies and stringent washing conditions. We performed photo-activated UV cross-linking using 4M-bM-^@M-^Y-thioruidine before cell lysis. Unspecific binding to the bead matrix and to the Fc part of the monoclonal rat antibody were recorded and corrected by empty bead controls and an antibody isotype control. Argonaute-associated miRNAs/mRNAs and unspecific bound miRNAs/mRNAs of the isotype control were identified by microarray hybridization. These experiments were performed in triplicates. AML-patient microRNAs: RNA extraction using the TRIzol protocol (Invitrogen), labeling of RNA with Cy3- (universal reference) and Cy5-Dyes (samples) using a truncated and mutated RNA ligase, hybridization of miRNAs over night at 42M-BM-0C using miRXplore microarrays and the a-Hyb Hybridization Station (MACS molecular Miltenyi Biotec)

Project description:PurposeMedulloblastoma comprises four distinct molecular subgroups: WNT, SHH, Group 3, and Group 4. Current medulloblastoma protocols stratify patients based on clinical features: patient age, metastatic stage, extent of resection, and histologic variant. Stark prognostic and genetic differences among the four subgroups suggest that subgroup-specific molecular biomarkers could improve patient prognostication.Patients and methodsMolecular biomarkers were identified from a discovery set of 673 medulloblastomas from 43 cities around the world. Combined risk stratification models were designed based on clinical and cytogenetic biomarkers identified by multivariable Cox proportional hazards analyses. Identified biomarkers were tested using fluorescent in situ hybridization (FISH) on a nonoverlapping medulloblastoma tissue microarray (n = 453), with subsequent validation of the risk stratification models.ResultsSubgroup information improves the predictive accuracy of a multivariable survival model compared with clinical biomarkers alone. Most previously published cytogenetic biomarkers are only prognostic within a single medulloblastoma subgroup. Profiling six FISH biomarkers (GLI2, MYC, chromosome 11 [chr11], chr14, 17p, and 17q) on formalin-fixed paraffin-embedded tissues, we can reliably and reproducibly identify very low-risk and very high-risk patients within SHH, Group 3, and Group 4 medulloblastomas.ConclusionCombining subgroup and cytogenetic biomarkers with established clinical biomarkers substantially improves patient prognostication, even in the context of heterogeneous clinical therapies. The prognostic significance of most molecular biomarkers is restricted to a specific subgroup. We have identified a small panel of cytogenetic biomarkers that reliably identifies very high-risk and very low-risk groups of patients, making it an excellent tool for selecting patients for therapy intensification and therapy de-escalation in future clinical trials.

Project description:Advances in transcriptomics have impacted the way of looking atimproved our understanding of leukemic development and helped enhancing the stratification of patients. Analyses of individual cohortsTranscriptomics studies often combined AML samples regardless of cytogenetic abnormalities. , which would lead to bias in Hence, deregulated genesdifferential gene expression analysis that may result from the differential representation of in less frequent AML subgroups have low weight, contrarily to those in abundant subgroups. We, thusHence, we performed a horizontal meta-analysis that integrated transcriptomic data of AML from multicentric multiple studies to enrich the less frequent cytogenetic subgroups and to uncover common genes involved in AML development and response to therapy. A total of 28 Affymetrix microarray datasets harboring 3940 AML samples were downloaded from the GEO database. After stringent quality control, transcriptomics data of 1523 samples from 11 datasets, covering 10 AML cytogenetic subgroups, were retained and merged with the transcriptomic data of 198 healthy bone marrow samples. Differentially expressed genes between each cytogenetic subgroup and normal samples were extracted, allowing the unbiased identification of 330 commonly deregulated genes (CODEGs)., which CODEGs showed enriched expression profiles in myeloid differentiation, leukemic stem cell status and relapse. Most of these genes were downregulated, in accordance with DNA hypermethylation. CODEGS were then used to create a prognostic score based on the weighted sum of expression of 22 core genes (CODEG22). The score was validated in on microarray data of five independent cohorts, and by qRT-PCR in a cohort of 142 samples, by qRT-PCR. CODEG22 stratified patients globally, as well as in subpopulations of cytologically normal and elderly patients. , and hence, couldSo, it may complement the European LeukemiaNet classification for a more accurate prediction of AML outcomes.

Dataset Information

MicroRNAs distinguish cytogenetic subgroups in pediatric AML and contribute to complex regulatory networks in AML-relevant pathways.

Background

Methodology/principal findings

Conclusions/significance

Publications

MicroRNAs distinguish cytogenetic subgroups in pediatric AML and contribute to complex regulatory networks in AML-relevant pathways.

Similar Datasets

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