Evidence map›Paper›PMID 26773058›Full record

ArticleNucleic acids research2016

CrossHub: a tool for multi-way analysis of The Cancer Genome Atlas (TCGA) in the context of gene expression regulation mechanisms.

George S Krasnov, Alexey A Dmitriev, Nataliya V Melnikova, Andrew R Zaretsky, Tatiana V Nasedkina, Alexander S Zasedatelev, Vera N Senchenko, Anna V Kudryavtseva

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
5.0field-weighted citation impact, top 4% 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

21 citing papers in PubMed, 39 citations in OpenAlex.

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  17. Viral component of the human genome.Molecular biology · 2017
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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

8 authors at 3 institutions in 1 country.

George S KrasnovEngelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia N.N. Blokhin Russian Cancer Research Center, Moscow 115478, Russia Orekhovich Institute of Biomedical Chemistry, Russian Academy of Medical Sciences, Moscow 119121, Russia.
Alexey A DmitrievEngelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia Alex_245@mail.ru.
Nataliya V MelnikovaEngelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia.
Andrew R ZaretskyM.M. Shemyakin-Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow 117997, Russia.
Tatiana V NasedkinaEngelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia N.N. Blokhin Russian Cancer Research Center, Moscow 115478, Russia.
Alexander S ZasedatelevEngelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia N.N. Blokhin Russian Cancer Research Center, Moscow 115478, Russia.
Vera N SenchenkoEngelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia.
Anna V KudryavtsevaEngelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia N.N. Blokhin Russian Cancer Research Center, Moscow 115478, Russia.
Engelhardt Institute of Molecular Biology · RURussian Cancer Research Center NN Blokhin · RUInstitute of Bioorganic Chemistry · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The contribution of different mechanisms to the regulation of gene expression varies for different tissues and tumors. Complementation of predicted mRNA-miRNA and gene-transcription factor (TF) relationships with the results of expression correlation analyses derived for specific tumor types outlines the interactions with functional impact in the current biomaterial. We developed CrossHub software, which enables two-way identification of most possible TF-gene interactions: on the basis of ENCODE ChIP-Seq binding evidence or Jaspar prediction and co-expression according to the data of The Cancer Genome Atlas (TCGA) project, the largest cancer omics resource. Similarly, CrossHub identifies mRNA-miRNA pairs with predicted or validated binding sites (TargetScan, mirSVR, PicTar, DIANA microT, miRTarBase) and strong negative expression correlations. We observed partial consistency between ChIP-Seq or miRNA target predictions and gene-TF/miRNA co-expression, demonstrating a link between these indicators. Additionally, CrossHub expression-methylation correlation analysis can be used to identify hypermethylated CpG sites or regions with the greatest potential impact on gene expression. Thus, CrossHub is capable of outlining molecular portraits of a specific gene and determining the three most common sources of expression regulation: promoter/enhancer methylation, miRNA interference and TF-mediated activation or repression. CrossHub generates formatted Excel workbooks with the detailed results. CrossHub is freely available athttps://sourceforge.net/projects/crosshub/.

Indexed as

Gene Expression Regulation, NeoplasticSoftwareBinding SitesChromatin ImmunoprecipitationDNA MethylationDown-RegulationGene Expression ProfilingGenome, HumanHumansMicroRNAsNeoplasmsSequence Analysis, DNATranscription FactorsMicroRNAsTranscription Factors

Identifiers

PMID26773058
PMCPMC4838350
OpenAlexW2234802731

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.