Dataset Information

MicroRNA profiling in pediatric pilocytic astrocytoma reveals biologically relevant targets, including PBX3, NFIB, and METAP2.

ABSTRACT: Pilocytic astrocytoma (PA) is a World Health Organization grade I glioma that occurs most commonly in children and young adults. Specific genetic alterations have been described in PA, but the pathogenesis remains poorly understood. We studied microRNA (miRNA) alterations in a large cohort of patients with PA. A total of 43 PA, including 35 sporadic grade I PA, 4 neurofibromatosis-1 (NF1)-associated PA, and 4 PA with pilomyxoid features, as well as 5 nonneoplastic brain controls were examined. BRAF fusion status was assessed in most cases. RNA was examined using the Agilent Human miRNA Microarray V3 platform. Expression of miRNA subsets was validated using quantitative real-time PCR (qRT-PCR) with Taqman probes. Validation of predicted protein targets was performed on tissue microarrays with the use of immunohistochemistry. We identified a subset of miRNAs that were differentially expressed in pediatric PAs versus normal brain tissue: 13 miRNAs were underexpressed, and 20 miRNAs were overexpressed in tumors. Differences were validated by qRT-PCR in a subset, with mean fold change in tumor versus brain of -17 (miR-124), -15 (miR-129), and 19.8 (miR-21). Searching for predicted protein targets in Targetscan, we identified a number of known and putative oncogenes that were predicted targets of miRNA sets relatively underexpressed in PA. Predicted targets with increased expression at the mRNA and/or protein level in PA included PBX3, METAP2, and NFIB. A unique miRNA profile exists in PA, compared with brain tissue. These miRNAs and their targets may play a role in the pathogenesis of PA.

SUBMITTER: Ho CY

PROVIDER: S-EPMC3534421 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

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MicroRNA profiling in pediatric pilocytic astrocytoma reveals biologically relevant targets, including PBX3, NFIB, and METAP2.

Ho Cheng-Ying CY Bar Eli E Giannini Caterina C Marchionni Luigi L Karajannis Matthias A MA Zagzag David D Gutmann David H DH Eberhart Charles G CG Rodriguez Fausto J FJ

Neuro-oncology 20121115 1

Pilocytic astrocytoma (PA) is a World Health Organization grade I glioma that occurs most commonly in children and young adults. Specific genetic alterations have been described in PA, but the pathogenesis remains poorly understood. We studied microRNA (miRNA) alterations in a large cohort of patients with PA. A total of 43 PA, including 35 sporadic grade I PA, 4 neurofibromatosis-1 (NF1)-associated PA, and 4 PA with pilomyxoid features, as well as 5 nonneoplastic brain controls were examined. B ...[more]

PMID: 23161775

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Project description:BACKGROUND:Protein-protein recognition is of fundamental importance in the vast majority of biological processes. However, it has already been demonstrated that it is very hard to distinguish true complexes from false complexes in so-called cross-docking experiments, where binary protein complexes are separated and the isolated proteins are all docked against each other and scored. Does this result, at least in part, reflect a physical reality? False complexes could reflect possible nonspecific or weak associations. RESULTS:In this paper, we investigate the twilight zone of protein-protein interactions, building on an interesting outcome of cross-docking experiments: false complexes seem to favor residues from the true interaction site, suggesting that randomly chosen partners dock in a non-random fashion on protein surfaces. Here, we carry out arbitrary docking of a non-redundant data set of 198 proteins, with more than 300 randomly chosen "probe" proteins. We investigate the tendency of arbitrary partners to aggregate at localized regions of the protein surfaces, the shape and compositional bias of the generated interfaces, and the potential of this property to predict biologically relevant binding sites. We show that the non-random localization of arbitrary partners after protein-protein docking is a generic feature of protein structures. The interfaces generated in this way are not systematically planar or curved, but tend to be closer than average to the center of the proteins. These results can be used to predict biological interfaces with an AUC value up to 0.69 alone, and 0.72 when used in combination with evolutionary information. An appropriate choice of random partners and number of docking models make this method computationally practical. It is also noted that nonspecific interfaces can point to alternate interaction sites in the case of proteins with multiple interfaces. We illustrate the usefulness of arbitrary docking using PEBP (Phosphatidylethanolamine binding protein), a kinase inhibitor with multiple partners. CONCLUSIONS:An approach using arbitrary docking, and based solely on physical properties, can successfully identify biologically pertinent protein interfaces.

Project description:BackgroundPilocytic Astrocytomas (PAs) are common low-grade central nervous system malignancies for which few recurrent and specific genetic alterations have been identified. In an effort to better understand the molecular biology underlying the pathogenesis of these pediatric brain tumors, we performed higher-order transcriptional network analysis of a large gene expression dataset to identify gene regulatory pathways that are specific to this tumor type, relative to other, more aggressive glial or histologically distinct brain tumours.MethodsRNA derived from frozen human PA tumours was subjected to microarray-based gene expression profiling, using Affymetrix U133Plus2 GeneChip microarrays. This data set was compared to similar data sets previously generated from non-malignant human brain tissue and other brain tumour types, after appropriate normalization.ResultsIn this study, we examined gene expression in 66 PA tumors compared to 15 non-malignant cortical brain tissues, and identified 792 genes that demonstrated consistent differential expression between independent sets of PA and non-malignant specimens. From this entire 792 gene set, we used the previously described PAP tool to assemble a core transcriptional regulatory network composed of 6 transcription factor genes (TFs) and 24 target genes, for a total of 55 interactions. A similar analysis of oligodendroglioma and glioblastoma multiforme (GBM) gene expression data sets identified distinct, but overlapping, networks. Most importantly, comparison of each of the brain tumor type-specific networks revealed a network unique to PA that included repressed expression of ONECUT2, a gene frequently methylated in other tumor types, and 13 other uniquely predicted TF-gene interactions.ConclusionsThese results suggest specific transcriptional pathways that may operate to create the unique molecular phenotype of PA and thus opportunities for corresponding targeted therapeutic intervention. Moreover, this study also demonstrates how integration of gene expression data with TF-gene and TF-TF interaction data is a powerful approach to generating testable hypotheses to better understand cell-type specific genetic programs relevant to cancer.

Dataset Information

MicroRNA profiling in pediatric pilocytic astrocytoma reveals biologically relevant targets, including PBX3, NFIB, and METAP2.

Publications

MicroRNA profiling in pediatric pilocytic astrocytoma reveals biologically relevant targets, including PBX3, NFIB, and METAP2.

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