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Identification of post-transcriptional regulatory networks during myeloblast-to-monocyte differentiation transition.

ABSTRACT: Treatment of leukemia cells with 1,25-dihydroxyvitamin D3 may overcome their differentiation block and lead to the transition from myeloblasts to monocytes. To identify microRNA-mRNA networks relevant for myeloid differentiation, we profiled the expression of mRNAs and microRNAs associated to the low- and high-density ribosomal fractions in leukemic cells and in their differentiated monocytic counterpart. Intersection between mRNAs shifted across the fractions after treatment with putative target genes of modulated microRNAs showed a series of molecular networks relevant for the monocyte cell fate determination, as for example the post-transcriptional regulation of the Polo-like kinase 1 (PLK1) by miR-22-3p and let-7e-5p.

SUBMITTER: Fontemaggi G

PROVIDER: S-EPMC4615388 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Identification of post-transcriptional regulatory networks during myeloblast-to-monocyte differentiation transition.

Fontemaggi Giulia G Bellissimo Teresa T Donzelli Sara S Iosue Ilaria I Benassi Barbara B Bellotti Giorgio G Blandino Giovanni G Fazi Francesco F

RNA biology 20150101 7

Treatment of leukemia cells with 1,25-dihydroxyvitamin D3 may overcome their differentiation block and lead to the transition from myeloblasts to monocytes. To identify microRNA-mRNA networks relevant for myeloid differentiation, we profiled the expression of mRNAs and microRNAs associated to the low- and high-density ribosomal fractions in leukemic cells and in their differentiated monocytic counterpart. Intersection between mRNAs shifted across the fractions after treatment with putative targe ...[more]

PMID: 25970317

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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

Identification of post-transcriptional regulatory networks during myeloblast-to-monocyte differentiation transition.

Publications

Identification of post-transcriptional regulatory networks during myeloblast-to-monocyte differentiation transition.

Similar Datasets

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