Evidence map›Paper›PMID 31758243›Full record

ArticleJournal of cancer research and clinical oncology2020

Candidate lncRNA-miRNA-mRNA network in predicting hepatocarcinogenesis with cirrhosis: an integrated bioinformatics analysis.

Rui Zhang, Ying-Yi Jiang, Kun Xiao, Xiao-Quan Huang, Jian Wang, Shi-Yao Chen

Open access · greenAbstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

12 citing papers in PubMed, 39 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. [Identification of onco-miRNAs in hepatocellular carcinoma and analysis of their regulatory network].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2022
    Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Identification of Potential Diagnostic and Prognostic Pseudogenes in Hepatocellular Carcinoma Based on Pseudogene-miRNA-mRNA Competitive Network.Medical science monitor : international medical journal of experimental and clinical research · 2020
    Article
  11. Article
  12. 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

6 authors at 1 institution in 1 country.

Rui ZhangDepartment of Gastroenterology and Hepatology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
Ying-Yi JiangDepartment of Gastroenterology and Hepatology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
Kun XiaoDepartment of Liver Surgery, Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
Xiao-Quan HuangDepartment of Gastroenterology and Hepatology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
Jian WangDepartment of Gastroenterology and Hepatology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
Shi-Yao ChenDepartment of Gastroenterology and Hepatology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China. chen.shiyao@zs-hospital.sh.cn.ORCID http://orcid.org/0000-0002-7276-1998
Fudan University · CN

Funding

Innovation Fund of Science and Technology Commission of Shanghai Municipality 17140902700Innovation Fund of Science and Technology Commission of Shanghai Municipality No. 15411950501, 15411950507
6 · The paper itself

Abstract

purposeThis study aimed to explore the potential competing endogenous RNA (ceRNA) network in forecasting HCC development in patients with cirrhosis through a comprehensive bioinformatic analysis.

methodsData mining from GEO and TCGA databases was employed to dig a spectrum of differentially expressed mRNA, lncRNA and miRNA profiles. Their expression was confirmed by RT-PCR in matched HCC cohorts (n = 6/group). The ceRNA network was constructed by co-expression analysis. Their reciprocal regulations and their roles in epithelial-to-mesenchymal transition (EMT) process were validated by gain- and loss-of-function experiments at the cellular level. Kaplan-Meier method was applied to reveal prognostic values.

resultsBy intersecting differentially expressed genes (DEGs) in GEO and TCGA data sets and Pearson correlation analysis, 20 mRNAs, 24 miRNAs and 41 lncRNAs were identified. Of these, FOXD2-AS1, BLVRA and CYTH2 were markedly upregulated in HCC tissues and HCC cells with high metastatic potential (MHCC97H) compared with their adjacent normal/cirrhotic tissues and L02 and MHCC97L cells. However, dysregulated miR-139-5p exhibited the opposite expression pattern. Using miRanda algorithms, FOXD2-AS1, BLVRA and CYTH2 showed potential binding sites for miR-139-5p. FOXD2-AS1 knockdown induced a marked increase in miR-139-5p and EMT inhibition. The loss of miR-139-5p led to an increase in BLVRA and CYTH2 expression and EMT process. Conversely, miR-139-5p overexpression suppressed BLVRA and CYTH expression and EMT process. FOXD2-AS1, miR-139-5p, BLVRA and CYTH2 highly correlated with prognosis in patients with HCC.

conclusionFOXD2-AS1/miR-139-5p/BLVRA or CYTH2 axis might be the underlying molecular mechanism that dissects HCC development caused by cirrhosis.

Indexed as

Carcinoma, HepatocellularCell LineCell Line, TumorCluster AnalysisComputational BiologyDatabases, GeneticData MiningGene Regulatory NetworksHumansLiver CirrhosisLiver NeoplasmsMicroRNAsRNA, Long NoncodingRNA, MessengerRNA, NeoplasmTranscriptomeMicroRNAsRNA, Long NoncodingRNA, MessengerRNA, NeoplasmBioinformaticsCirrhosisDifferentially expressed genesHepatocellular carcinomaLong non-coding RNAsmiRNAs

Identifiers

PMID31758243
PMCPMC11804427
OpenAlexW2991355652

What OpenQuestion holds

Textmetadata
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.