MiRNA profiling of human umbilical cord derived mesenchymal stem cells in the process of smooth muscle cell differentiation
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Wenduo Gu
PROVIDER: E-MTAB-6393 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:The identification of deregulated miRNA in multiple myeloma (MM) has progressively added a further level of complexity to MM biology. In the present study, we take virtue of in silico integrative genomics analysis to generate an unprecedented global view of the transcriptional regulatory networks modulated in MM to define microRNAs impacting in regulatory circuits with potential functional and clinical relevance. miRNA and gene expression profiles in two large representative MM datasets, available from retrospective and prospective clinical trials and encompassing a total of 249 patients at diagnosis, were analyzed by means of two robust computational procedure to identify (i) relevant miRNA/transcription factors/target gene circuits in the disease and (ii) highly modulated miRNA-gene networks in those pathways enriched with miRNA-target gene interactions in specific MM subgroups. The analysis reinforced the pivotal role the miRNA cluster miR-99b/let-7e/miR-125a, specifically deregulated in MM patients with t(4;14) translocation, and disentangled its major relationships with transcriptional relevance. Integrated pathway analyses performed on the expression data of the MM patients stratified according to t(4;14) further allowed to define the pathway composed by the interactions that mainly characterize this MM subset and unravel connected pathways with putative role in the tumor biology. miRNA and transcripts expression data were analyzed using MAGIA2, to identify mixed circuits (triplets) involving miRNA/gene/transcription factor (TF; http://gencomp.bio.unipd.it/magia2/), as previously described [Bisognin A et al, 2012, Nucl Acid Res]. Specifically, Targetscan was used as target prediction algorithm, and Pearson coefficient was used to measure relationships between microRNA and target mRNA expression profiles. Only the most variable 75% genes according to the coefficient of variation were considered. Lower threshold for absolute correlation coefficients within circuits was set to 0.2; 0.4 was used for miRNA/target binary relationships. Micrographite pipeline allows integrating pathway topologies with predicted and validated miRNAâtarget interactions, to perform integrated analyses of miRNA and gene expression profiles, for the identification of modulated regulatory circuits involved in the disease in terms of both expression variations and differential strength of inferred interactions [Calura E et al, 2014, Nucl Acid Res]. Micrographite has two steps: i) the extension of pathway annotation using miRNA-target interaction and ii) recursive topological pathway analysis on these networks. We considered network topologies derived from KEGG database by Graphite package [Sales G et al, 2012, BMC Bioinformatics] and miRNA-target gene interactions identified by the above-described MAGIA2 analysis. Specifically, a miRNA was added to a pathway-derived network only if one (or more) of its validated or predicted target genes is a pathway component. Then, a modified recursive version of CliPPER topological pathway analysis [Martini P et al, 2013; Nucl Acid Res] was applied to the composite network, as previously described [Calura E et al, 2014, Nucl Acid Res] in order to identify the most important and non-redundant circuit modulated across groups. Briefly, (i) in the first step, the most significant pathways were selected using P<0.1 as cut-off value for significance; (ii) for each dataset, the upper-scored 10th percentile of the portion of these previously selected pathways (i.e. âpathsâ, calculated over a 10,000-permutation step) mostly associated with phenotype were selected; and (iii) for each dataset a meta-pathway was assembled using the paths extracted from previous step and finally re-analyzed GSE70254 and GSE70319 Samples with the same patient number represent the same sample, profiled using two different Platforms.
2015-12-08 | E-GEOD-70254 | biostudies-arrayexpress
Project description:The identification of deregulated miRNA in multiple myeloma (MM) has progressively added a further level of complexity to MM biology. In the present study, we take virtue of in silico integrative genomics analysis to generate an unprecedented global view of the transcriptional regulatory networks modulated in MM to define microRNAs impacting in regulatory circuits with potential functional and clinical relevance. miRNA and gene expression profiles in two large representative MM datasets, available from retrospective and prospective clinical trials and encompassing a total of 249 patients at diagnosis, were analyzed by means of two robust computational procedure to identify (i) relevant miRNA/transcription factors/target gene circuits in the disease and (ii) highly modulated miRNA-gene networks in those pathways enriched with miRNA-target gene interactions in specific MM subgroups. The analysis reinforced the pivotal role the miRNA cluster miR-99b/let-7e/miR-125a, specifically deregulated in MM patients with t(4;14) translocation, and disentangled its major relationships with transcriptional relevance. Integrated pathway analyses performed on the expression data of the MM patients stratified according to t(4;14) further allowed to define the pathway composed by the interactions that mainly characterize this MM subset and unravel connected pathways with putative role in the tumor biology. miRNA and transcripts expression data were analyzed using MAGIA2, to identify mixed circuits (triplets) involving miRNA/gene/transcription factor (TF; http://gencomp.bio.unipd.it/magia2/), as previously described [Bisognin A et al., 2012, Nucl Acid Res]. Specifically, Targetscan was used as target prediction algorithm, and Pearson coefficient was used to measure relationships between microRNA and target mRNA expression profiles. Only the most variable 75% genes according to the coefficient of variation were considered. Lower threshold for absolute correlation coefficients within circuits was set to 0.2; 0.4 was used for miRNA/target binary relationships. Micrographite pipeline allows integrating pathway topologies with predicted and validated miRNA-target interactions, to perform integrated analyses of miRNA and gene expression profiles, for the identification of modulated regulatory circuits involved in the disease in terms of both expression variations and differential strength of inferred interactions [Calura E et al., 2014, Nucl Acid Res]. Micrographite has two steps: i) the extension of pathway annotation using miRNA-target interaction and ii) recursive topological pathway analysis on these networks. We considered network topologies derived from KEGG database by Graphite package [Sales G et al., 2012, BMC Bioinformatics] and miRNA-target gene interactions identified by the above-described MAGIA2 analysis. Specifically, a miRNA was added to a pathway-derived network only if one (or more) of its validated or predicted target genes is a pathway component. Then, a modified recursive version of CliPPER topological pathway analysis [Martini P et al., 2013; Nucl Acid Res] was applied to the composite network, as previously described [Calura E et al., 2014, Nucl Acid Res] in order to identify the most important and non-redundant circuit modulated across groups. Briefly, (i) in the first step, the most significant pathways were selected using P<0.1 as cut-off value for significance; (ii) for each dataset, the upper-scored 10th percentile of the portion of these previously selected pathways (i.e. paths, calculated over a 10,000-permutation step) mostly associated with phenotype were selected; and (iii) for each dataset a meta-pathway was assembled using the paths extracted from previous step and finally re-analyzed. GSE73452 and GSE73454 Samples with the same patient number represent the same sample, profiled using two different Platforms.
2015-12-08 | E-GEOD-73454 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2015-12-15 | E-GEOD-70323 | biostudies-arrayexpress
Project description:C57BL/6 mice were either given Staphyloccocal entertoxin B (SEB) or PBS as a control for 48 hours. Mice were sacrificed and lung infiltrating mononuclear cells were isolated. Total RNA extraction was performed using Qiagen miRNeasy kit and RNA quality was assessed specrophotometrically. Affymetric Gene Chip miRNA 1.0 array was used for miRNA profiling using FlashTag Biotin HSR RNA labeling kit.
2014-04-01 | E-MTAB-2379 | biostudies-arrayexpress
Project description:Multilineage-differentiating stress enduring (Muse) cells are nontumorigenic endogenous pluripotent-like stem cells easily collected from various adult or fetal tissues. The tissue regenerative effects of Muse cells have been demonstrated in many disease models, as they reach damaged sites after intravenous injection to exert pleiotropic effects. Previous reports indicate that several human tissues are readily accessible for Muse cell isolation, including adult tissues such as bone marrow (BM) and embryonic tissues such as Wharton’s Jelly (WJ) from umbilical cord. Wa analyzed the protein repertoires of WJ-Muse and BM-Muse using mass spectrometry-based proteomics.
2023-07-17 | PXD036883 | Pride
Project description:We compared 15 severely diseased aortic valve sample to 16 control aortic valve samples using microRNA microarrays (Affymetrix GeneChip miRNA 2.0). The diseased samples were taken from areas of severe disease of aortic valves removed at aortic valve replacement for severe aortic stenosis. Control samples were obtained from macroscopically normal post-mortem aortic valves. In addition, we compared areas of mild or moderate disease on valves from participants with severe aortic stenosis to the same participant's severely diseased sample in seven participants.
2017-04-27 | E-MTAB-2766 | biostudies-arrayexpress
Project description:We compared the circulating plasma microRNA profile in EDTA plasma in patients with aortic stenosis to a control group.
2015-08-25 | E-MTAB-2785 | biostudies-arrayexpress
Project description:Analysis of the effect of all available statins (atorvastatin, lovastatin, simvastatin, fluvastatin, cerivastatin, pravastatin, rosuvastatin, and pitavastatin) on the expression of genes in human cell cultures to investigate potential anti-inflammatory effect during COVID-19 disease. Transcription profiling was done using microarray assay.
2024-01-01 | E-MTAB-11579 | biostudies-arrayexpress
Project description:We performed a proteomic profiling of human mesenchymal stem cells (hMSCs) derived from adipose tissue or umbilical cord.
2018-07-11 | PXD009893 | Pride
Project description:Why ~70% of women with polycystic ovary syndrome (PCOS) have intrinsic insulin resistance (IR), above and beyond that associated with body mass, including dysfunctional glucose metabolism in adipose tissue (AT), remains a fundamental question. In these experiments, we sought to explore the role of miRNAs in the AT of PCOS and matched controls. Analysis determined that PCOS AT has a differentially expressed miRNA profile, including upregulated miR-93. We observed a significant association between HOMA-IR, and GLUT4 and miR-93 expression in human AT. Our results point to a novel mechanism for regulating insulin-stimulated glucose uptake via miR-93, and demonstrate upregulated miR-93 expression in PCOS, possibly accounting for the IR of the syndrome, and also in non-PCOS women with IR. We performed miRNA microarrays to determine PCOS-related miRNA expression in adipose derived from lean PCOS patients and matched control women. We analyized miRNA from total RNA extracted from subcutaneous (sc) adipose tissue from three lean PCOS patients and three matched control women.
2012-09-06 | E-GEOD-37914 | biostudies-arrayexpress