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Integrated approaches to miRNAs target definition: time-series analysis in an osteosarcoma differentiative model

Overview of attention for article published in BMC Medical Genomics, June 2015
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Title
Integrated approaches to miRNAs target definition: time-series analysis in an osteosarcoma differentiative model
Published in
BMC Medical Genomics, June 2015
DOI 10.1186/s12920-015-0106-0
Pubmed ID
Authors

A. Grilli, M. Sciandra, M. Terracciano, P. Picci, K. Scotlandi

Abstract

microRNAs (miRs) are small non-coding RNAs involved in the fine regulation of several cellular processes by inhibiting their target genes at post-transcriptional level. Osteosarcoma (OS) is a tumor thought to be related to a molecular blockade of the normal process of osteoblast differentiation. The current paper explores temporal transcriptional modifications comparing an osteosarcoma cell line, Saos-2, and clones stably transfected with CD99, a molecule which was found to drive OS cells to terminally differentiate. Parental cell line and CD99 transfectants were cultured up to 14 days in differentiating medium. In this setting, OS cells were profiled by gene and miRNA expression arrays. Integration of gene and miRNA profiling was performed by both sequence complementarity and expression correlation. Further enrichment and network analyses were carried out to focus on the modulated pathways and on the interactions between transcriptome and miRNome. To track the temporal transcriptional modification, a PCA analysis with differentiated human MSC was performed. We identified a strong (about 80 %) gene down-modulation where reversion towards the osteoblast-like phenotype matches significant enrichment in TGFbeta signaling players like AKT1 and SMADs. In parallel, we observed the modulation of several cancer-related microRNAs like miR-34a, miR-26b or miR-378. To decipher their impact on the modified transcriptional program in CD99 cells, we correlated gene and microRNA time-series data miR-34a, in particular, was found to regulate a distinct subnetwork of genes with respect to the rest of the other differentially expressed miRs and it appeared to be the main mediator of several TGFbeta signaling genes at initial and middle phases of differentiation. Integration studies further highlighted the involvement of TGFbeta pathway in the differentiation of OS cells towards osteoblasts and its regulation by microRNAs. These data underline that the expression of miR-34a and down-modulation of TGFbeta signaling emerge as pivotal events to drive CD99-mediated reversal of malignancy and activation of differentiation in OS cells. Our results describe crucial and specific interacting actors providing and supporting their relevance as potential targets for therapeutic differentiative strategies.

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 4%
Unknown 23 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 25%
Researcher 5 21%
Student > Bachelor 3 13%
Student > Ph. D. Student 3 13%
Student > Postgraduate 2 8%
Other 2 8%
Unknown 3 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 38%
Agricultural and Biological Sciences 6 25%
Medicine and Dentistry 4 17%
Immunology and Microbiology 1 4%
Engineering 1 4%
Other 0 0%
Unknown 3 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 July 2015.
All research outputs
#16,099,609
of 23,881,329 outputs
Outputs from BMC Medical Genomics
#701
of 1,268 outputs
Outputs of similar age
#156,544
of 265,309 outputs
Outputs of similar age from BMC Medical Genomics
#21
of 31 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,268 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 34th percentile – i.e., 34% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 265,309 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.