Evidence map›Paper›PMID 31543683›Full record

ArticleWorld journal of gastroenterology2019

Identification of hepatitis B virus and liver cancer bridge molecules based on functional module network.

Xiao-Bing Huang, Yong-Gang He, Lu Zheng, Huan Feng, Yu-Ming Li, Hong-Yan Li, Feng-Xia Yang, Jing Li

Open access · hybridAbstract read
In one paragraph

Article in World journal of gastroenterology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 32% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

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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 1 institution in 1 country.

Xiao-Bing HuangDepartment of Hepatobiliary Surgery, Second Hospital Affiliated to Third Military Medical University of Xinqiao Hospital, Chongqing 400037, China.
Yong-Gang HeDepartment of Hepatobiliary Surgery, Second Hospital Affiliated to Third Military Medical University of Xinqiao Hospital, Chongqing 400037, China.
Lu ZhengDepartment of Hepatobiliary Surgery, Second Hospital Affiliated to Third Military Medical University of Xinqiao Hospital, Chongqing 400037, China.
Huan FengDivision of Nursing, Second Hospital Affiliated to Third Military Medical University, Xinqiao Hospital, Chongqing 400037, China.
Yu-Ming LiDepartment of Hepatobiliary Surgery, Second Hospital Affiliated to Third Military Medical University of Xinqiao Hospital, Chongqing 400037, China.
Hong-Yan LiDepartment of Hepatobiliary Surgery, Second Hospital Affiliated to Third Military Medical University of Xinqiao Hospital, Chongqing 400037, China.
Feng-Xia YangDepartment of Hepatobiliary Surgery, Second Hospital Affiliated to Third Military Medical University of Xinqiao Hospital, Chongqing 400037, China.
Jing LiDepartment of Hepatobiliary Surgery, Second Hospital Affiliated to Third Military Medical University of Xinqiao Hospital, Chongqing 400037, China. xqyylijing@tom.com.
Army Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe potential role of chronic inflammation in the development of cancer has been widely recognized. However, there has been little research fully and thoroughly exploring the molecular link between hepatitis B virus (HBV) and hepatocellular carcinoma (HCC).

aimTo elucidate the molecular links between HBV and HCC through analyzing the molecular processes of HBV-HCC using a multidimensional approach.

methodsFirst, maladjusted genes shared between HBV and HCC were identified by disease-related differentially expressed genes. Second, the protein-protein interaction network based on dysfunctional genes identified a series of dysfunctional modules and significant crosstalk between modules based on the hypergeometric test. In addition, key regulators were detected by pivot analysis. Finally, targeted drugs that have regulatory effects on diseases were predicted by modular methods and drug target information.

resultsThe study found that 67 genes continued to increase in the HBV-HCC process. Moreover, 366 overlapping genes in the module network participated in multiple functional blocks. It could be presumed that these genes and their interactions play an important role in the relationship between inflammation and cancer. Correspondingly, significant crosstalk constructed a module level bridge for HBV-HCC molecular processes. On the other hand, a series of non-coding RNAs and transcription factors that have potential pivot regulatory effects on HBV and HCC were identified. Among them, some of the regulators also had persistent disorders in the process of HBV-HCC including microRNA-192, microRNA-215, and microRNA-874, and early growth response 2, FOS, and Kruppel-like factor 4. Therefore, the study concluded that these pivots are the key bridge molecules outside the module. Last but not least, a variety of drugs that may have some potential pharmacological or toxic side effects on HBV-induced HCC were predicted, but their mechanisms still need to be further explored.

conclusionThe results suggest that the persistent inflammatory environment of HBV can be utilized as an important risk factor to induce the occurrence of HCC, which is supported by molecular evidence.

Indexed as

Carcinoma, HepatocellularDatasets as TopicGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHepatitis B, ChronicHepatitis B virusHost-Pathogen InteractionsHumansImmunoglobulin GKruppel-Like Factor 4Liver NeoplasmsMelphalanMicroRNAsProtein Interaction MappingProtein Interaction Mapsantineoplastic agent K 18Immunoglobulin GKLF4 protein, humanKruppel-Like Factor 4MelphalanMicroRNAsTranscription FactorsHepatitis B virusHepatocellular carcinomaMolecular linkagenon-coding RNATranscription factors

Identifiers

PMID31543683
PMCPMC6737318
OpenAlexW2972024120

What OpenQuestion holds

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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.