Co-expression analysis and ceRNA network reveal eight novel potential lncRNA biomarkers in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the most common primary liver cancer in the world, with a high degree of malignancy and recurrence. The influence of the ceRNA network in tumor on the biological function of liver cancer is very important, It has been reported that many lncRNA play a key role in liver cancer development. In our study, integrated data analysis revealed potential eight novel lncRNA biomarkers in hepatocellular carcinoma. METHODS: Transcriptome data and clinical data were downloaded from the The Cancer Genome Atlas (TCGA) data portal. Weighted gene co-expression network analysis was performed to identify the expression pattern of genes in liver cancer. Then, the ceRNA network was constructed using transcriptome data. RESULTS: The integrated analysis of miRNA and RNAseq in the database show eight novel lncRNAs that may be involved in important biological pathways, including TNM and disease development in liver cancer. We performed function enrichment analysis of mRNAs affected by these lncRNAs. CONCLUSIONS: By identifying the ceRNA network and the lncRNAs that affect liver cancer, we showed that eight novel lncRNAs play an important role in the development and progress of liver cancer.

Identification of metabolism-associated pathways and genes involved in male and female liver cancer patients.

Hepatocellular carcinoma (HCC) is a major type of primary liver cancer. HCC is influenced by sex and multiple metabolic abnormalities. The present study aimed to compare the overall metabolic changes between male and female HCC patients and identify key metabolic genes. Metabolic genes and pathways were identified based on analyses of publicly available data. Differential expression analysis, gene set enrichment analysis, survival analysis and transcriptional regulation analysis were employed to explore sex differences and identify key metabolic genes in HCC. The results suggested that female patients had more severe metabolic gene expression abnormalities and pathway deregulation than male patients. This study identified 9 key metabolic genes, and only upregulated ALDH1A2 independently increased overall survival risk in patients. Bioinformatic analyses suggest that upregulated GATA3 and TAL1 activate ALDH1A2 and then disrupt amino acid and carbohydrate metabolism, which may increase the risk of HCC. This study identified a novel contribution of upregulated ALDH1A2 to HCC. Future studies are needed to elucidate the potential metabolic mechanism of the role of ALDH1A2 in HCC.