Evidence map›Paper›PMID 31477006›Full record

ArticleBMC bioinformatics2019

Analyzing the regulation of miRNAs on protein-protein interaction network in Hodgkin lymphoma.

Huimin Lei, Wenxu Liu, Jiarui Si, Ju Wang, Tao Zhang

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 47% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
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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

5 authors at 1 institution in 1 country.

Huimin LeiSchool of Biomedical Engineering, Tianjin Medical University, Tianjin, China.
Wenxu LiuSchool of Biomedical Engineering, Tianjin Medical University, Tianjin, China.
Jiarui SiSchool of Basic Medicine, Tianjin Medical University, Tianjin, China.
Ju WangSchool of Biomedical Engineering, Tianjin Medical University, Tianjin, China.
Tao ZhangSchool of Biomedical Engineering, Tianjin Medical University, Tianjin, China. zhangtao@tijmu.edu.cn.ORCID http://orcid.org/0000-0003-3414-7820
Tianjin Medical University · CN

Funding

China Postdoctoral Science Foundation 2013M530878China Postdoctoral Science Foundation 2017M621092
6 · The paper itself

Abstract

backgroundHodgkin Lymphoma (HL) is a type of aggressive malignancy in lymphoma that has high incidence in young adults and elderly patients. Identification of reliable diagnostic markers and efficient therapeutic targets are especially important for the diagnosis and treatment of HL. Although many HL-related molecules have been identified, our understanding on the molecular mechanisms underlying the disease is still far from complete due to its complex and heterogeneous characteristics. In such situation, exploring the molecular mechanisms underlying HL via systems biology approaches provides a promising option. In this study, we try to elucidate the molecular mechanisms related to the disease and identify potential pharmaceutical targets from a network-based perspective.

resultsWe constructed a series of network models. Based on the analysis of these networks, we attempted to identify the biomarkers and elucidate the molecular mechanisms underlying HL. Initially, we built three different but related protein networks, i.e., background network, HL-basic network and HL-specific network. By analyzing these three networks, we investigated the connection characteristic of the HL-related proteins. Subsequently, we explored the miRNA regulation on HL-specific network and analyzed three kinds of simple regulation patterns, i.e., co-regulation of protein pairs, as well as the direct and indirect regulation of triple proteins. Finally, we constructed a simplified protein network combined with the regulation of miRNAs on proteins to better understand the relation between HL-related proteins and miRNAs.

conclusionsWe find that the HL-related proteins are more likely to connect with each other compared to other proteins. Moreover, the HL-specific network can be further divided into five sub-networks and 49 proteins as the backbone of HL-specific network make up and connect these 5 sub-networks. Thus, they may be closely associated with HL. In addition, we find that the co-regulation of protein pairs is the main regulatory pattern of miRNAs on the protein network in the HL-specific network. According to the regulation of miRNA on protein network, we have identified 5 core miRNAs as the potential biomarkers for diagnostic of HL. Finally, several protein pathways have been identified to closely associated with HL, which provides deep insights into underlying mechanism of HL.

Indexed as

Gene Expression Regulation, NeoplasticGene Regulatory NetworksProtein Interaction MapsBiomarkers, TumorGene Expression ProfilingHodgkin DiseaseHumansMicroRNAsSystems BiologyBiomarkers, TumorMicroRNAsHodgkin LymphomamiRNA regulationNetwork analysisProtein interaction network

Identifiers

PMID31477006
PMCPMC6720096
OpenAlexW2971188062

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.