Dataset Information

MiRNA profiles of HCC from Southeast China

ABSTRACT: We evaluated the expression of known human miRNAs in human hepatocellular carcinoma (HCC) and normal hepatic tissues from southeast China, and identified the differentially expressed miRNAs in HCC tissues. We use microRNA array platform from CapitalBio Corp. to access the miRNA expression profiles in HCC and non-tumor liver samples from Southeast China. There were 5 HCC samples and 3 non-tumor liver samples in our study. As the microarray platform we used was based on a older version of miRBase, we mapped the probe sequences to a newer version of miRBase before these data was applied to further analysis.

ORGANISM(S): Homo sapiens

SUBMITTER:

PROVIDER: S-DIXA-D-1012 | biostudies-other |

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description: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.

Dataset Information

MiRNA profiles of HCC from Southeast China

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure