ArticleBioscience reports2020
Potential targets and molecular mechanism of miR-331-3p in hepatocellular carcinoma identified by weighted gene coexpression network analysis.
Article in Bioscience reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Spliceosome protein EFTUD2: A potential pathogenetic factor in tumorigenesis and some developmental defects (Review).Molecular medicine reports · 2025Review
- TMSB4X is a regulator of inflammation-associated ferroptosis, and promotes the proliferation, migration and invasion of hepatocellular carcinoma cells.Discover oncology · 2024Article
- Study on the molecular mechanism of nightshade in the treatment of colon cancer.Bioengineered · 2022Article
- Over-activation of EFTUD2 correlates with tumor propagation and poor survival outcomes in hepatocellular carcinoma.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2022Article
- Identification of Biomarkers Related to Immune Cell Infiltration in Hepatocellular Carcinoma Using Gene Co-Expression Network.Pathology oncology research : POR · 2021Article
- Comprehensive analysis of the functions and prognostic significance of RNA-binding proteins in bladder urothelial carcinoma.American journal of translational research · 2020Article
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Authors and funding
5 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hepatocellular carcinoma (HCC) is one of the most common malignant tumor. miR-331-3p has been reported relevant to the progression of HCC, but the molecular mechanism of its regulation is still unclear. In the study, we comprehensively studied the role of miR-331-3p in HCC through weighted gene coexpression network analysis (WGCNA) based on The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and Oncomine. WGCNA was applied to build gene co-expression networks to examine the correlation between gene sets and clinical characteristics, and to identify potential biomarkers. Five hundred one target genes of miR-331-3p were obtained by overlapping differentially expressed genes (DEGs) from the TCGA database and target genes predicted by miRWalk. The critical turquoise module and its eight key genes were screened by WGCNA. Enrichment analysis was implemented based on the genes in the turquoise module. Moreover, 48 genes with a high degree of connectivity were obtained by protein-protein interaction (PPI) analysis of the genes in the turquoise module. From overlapping genes analyzed by WGCNA and PPI, two hub genes were obtained, namely coatomer protein complex subunit zeta 1 (COPZ1) and elongation factor Tu GTP binding domain containing 2 (EFTUD2). In addition, the expression of both hub genes was also significantly higher in tumor tissues compared with normal tissues, as confirmed by analysis based on TCGA and Oncomine. Both hub genes were correlated with poor prognosis based on TCGA data. Receiver operating characteristic (ROC) curve validated that both hub genes exhibited excellent diagnostic efficiency for normal and tumor tissues.
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