Evidence map›Paper›PMID 26123714›Full record

ArticleBMC medical genomics2015

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

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

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 28% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Navigating the genomic instability mine field of osteosarcoma to better understand implications of non-coding RNAs.Biocell : official journal of the Sociedades Latinoamericanas de Microscopia Electronica ... et. al · 2022
    Article
  4. Article
  5. Article
  6. RSC advances · 2018
    Article
  7. Oncotarget · 2017
    Article
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

A GrilliLaboratory of Experimental Oncology, CRS Development of Biomolecular Therapies, Rizzoli Orthopedic Institute, Via di Barbiano 1/10, 40136, Bologna, Italy. andrea.grilli@ior.it.
M SciandraLaboratory of Experimental Oncology, CRS Development of Biomolecular Therapies, Rizzoli Orthopedic Institute, Via di Barbiano 1/10, 40136, Bologna, Italy. marika.sciandra@ior.it.
M TerraccianoLaboratory of Experimental Oncology, CRS Development of Biomolecular Therapies, Rizzoli Orthopedic Institute, Via di Barbiano 1/10, 40136, Bologna, Italy. mario.terracciano83@gmail.com.
P PicciLaboratory of Experimental Oncology, CRS Development of Biomolecular Therapies, Rizzoli Orthopedic Institute, Via di Barbiano 1/10, 40136, Bologna, Italy. piero.picci@ior.it.
K ScotlandiLaboratory of Experimental Oncology, CRS Development of Biomolecular Therapies, Rizzoli Orthopedic Institute, Via di Barbiano 1/10, 40136, Bologna, Italy. katia.scotlandi@ior.it.
Istituto Ortopedico Rizzoli · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundmicroRNAs (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.

methodsParental 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.

resultsWe 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.

conclusionsThese 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.

Indexed as

Gene Expression Profiling12E7 AntigenAntigens, CDCell Adhesion MoleculesCell DifferentiationCell Line, TumorClone CellsDown-RegulationHumansMicroRNAsOsteoblastsOsteosarcomaPhenotypeRNA, MessengerSignal TransductionTime Factors12E7 AntigenAntigens, CDCD99 protein, humanCell Adhesion MoleculesMicroRNAsMIRN34 microRNA, humanRNA, MessengerTransforming Growth Factor beta

Identifiers

PMID26123714
PMCPMC4486310
OpenAlexW1900209405

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.