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Published on: August 1, 2018
In silico analysis excavates potential biomarkers by constructing miRNA-mRNA networks between non-cirrhotic HCC and
Bisha Ding1, Weiyang Lou1, Jingxing Liu2
11Program of Innovative Cancer Therapeutics, Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, College of Medicine, Key Laboratory of Combined Multi-Organ Transplantation, Ministry of Public Health, Key Laboratory of Organ Transplantation, Zhejiang University, Hangzhou, 310003 Zhejiang Province China.
Insights
This study reveals key gene and microRNA differences between non-cirrhotic and cirrhotic hepatocellular carcinoma (HCC). These findings help understand HCC molecular mechanisms and develop targeted therapies.
Area of Science:
- Oncology
- Molecular Biology
- Bioinformatics
Background:
- Hepatocellular carcinoma (HCC) patients with or without cirrhosis exhibit distinct clinical features, tumor progression, and prognoses.
- Limited research has explored the molecular mechanisms differentiating cirrhotic and non-cirrhotic HCC.
Purpose of the Study:
- To investigate the molecular mechanisms underlying hepatocellular carcinoma (HCC) in patients with and without cirrhosis.
- To construct microRNA-mRNA regulatory networks for non-cirrhotic and cirrhotic HCC.
Main Methods:
- Utilized The Cancer Genome Atlas (TCGA) database for clinical and RNA-seq data.
- Identified differentially expressed genes (DEGs) and constructed protein-protein interaction (PPI) networks.
- Predicted microRNAs (miRNAs) targeting key genes and validated their expression and regulatory relationships using bioinformatics tools and qRT-PCR.
Main Results:
- Identified 768 DEGs, primarily in the neuroactive ligand-receptor interaction pathway.
- Selected five key genes (CCL19, CCL25, CNR1, PF4, PPBP) with diagnostic value in specific HCC subtypes.
- Constructed potential miRNA-mRNA networks, identifying four miRNAs with high research value.
Conclusions:
- This study provides the first in silico construction of miRNA-mRNA regulatory networks for non-cirrhotic and cirrhotic HCC.
- The identified key genes and miRNAs offer potential biomarkers for HCC diagnosis and therapeutic targets.
Background:
Mounting evidences have demonstrated that HCC patients with or without cirrhosis possess different clinical characteristics, tumor development and prognosis. However, few studies directly investigated the underlying molecular mechanisms between non-cirrhotic HCC and cirrhotic HCC.
Methods:
The clinical information and RNA-seq data were downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) of HCC with or without cirrhosis were obtained by R software. Functional annotation and pathway enrichment analysis were performed by Enrichr. Protein-protein interaction (PPI) network was established through STRING and mapped to Cytoscape to identify hub genes. MicroRNAs were predicted through miRDB database. Furthermore, correlation analysis between selected genes and miRNAs were conducted via starBase database. MiRNAs expression levels between HCC with or without cirrhosis and corresponding normal liver tissues were further validated through GEO datasets. Finally, expression levels of key miRNAs and target genes were validated through qRT-PCR.
Results:
Between 132 non-cirrhotic HCC and 79 cirrhotic HCC in TCGA, 768 DEGs were acquired, mainly involved in neuroactive ligand-receptor interaction pathway. According to the result from gene expression analysis in TCGA, CCL19, CCL25, CNR1, PF4 and PPBP were renamed as key genes and selected for further investigation. Survival analysis indicated that upregulated CNR1 correlated with worse OS in cirrhotic HCC. Furthermore, ROC analysis revealed the significant diagnostic values of PF4 and PPBP in cirrhotic HCC, and CCL19, CCL25 in non-cirrhotic HCC. Next, 517 miRNAs were predicted to target the 5 key genes. Correlation analysis confirmed that 16 of 517 miRNAs were negatively regulated the key genes. By detecting the expression levels of these key miRNAs from GEO database, we found 4 miRNAs have high research values. Finally, potential miRNA-mRNA networks were constructed based on the results of qRT-PCR.
Conclusion:
In silico analysis, we first constructed the miRNA-mRNA regulatory networks in non-cirrhotic HCC and cirrhotic HCC.
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