Published online Jul 15, 2022. doi: 10.4251/wjgo.v14.i7.1265
Peer-review started: January 25, 2022
First decision: May 9, 2022
Revised: May 18, 2022
Accepted: June 26, 2022
Article in press: June 26, 2022
Published online: July 15, 2022
Liver fibrosis and hepatocellular carcinoma (HCC) are common adverse consequences of chronic liver injury. Establishing more effective biomarkers is important for understanding the pathogenesis, occurrence, development mechanisms of liver fibrosis and HCC, as well as to identify new diagnostic and therapeutic tools.
Bioinformatics has screened out many differentially expressed genes related to liver fibrosis; however, it is unknown whether these genes are different in animal and human liver fibrosis tissues, especially among the different fibrotic degrees. Therefore, we should carefully analyze the research results of bioinformatics.
To identify liver fibrosis-related core genes, we observed and compared the differential expression pattern of core genes in patients with liver fibrosis and HCC.
In this study, we analyzed the expression pattern of hub genes of fibrosis and HCC. Bioinformatics analyses, quantitative polymerase chain reaction, Western blot, and immunohistochemistry of liver tissues from mouse model and patients were performed to identify novel biomarkers of liver fibrosis and HCC.
Ten hub genes (CXCL9, CXCL10, CXCR4, DCN, DPT, LAMA2, LUM, MFAP4, PDGFRA, and SOX9) associated with cirrhosis were screened from GSE14323, GSE36411, and GSE89377 datasets. DCN, DPT, and SOX9 were highly expressed in the CCl4-induced mouse model of liver cirrhosis and fibrotic patient liver samples, and their expression levels were associated with the degree of fibrosis. In patients with HCC, SOX9 was upregulated, while DCN and DPT were downregulated. However, the 5-year survival rate of HCC patients with high SOX 9 expression was significantly reduced, which is different from DPT or DCN.
We screened and identified 10 hub genes related to fibrosis. The expression levels of DCN, DPT, and SOX were positively correlated with the degree of liver fibrosis but showed different correlations with the survival rate of patients with HCC.
The integrated approach of bioinformatics and molecular biology is more efficient to research multi-factorial diseases, such as liver fibrosis and liver cancer. Future studies on the differences on DCN, DPT, and SOX9 expression may help in the better understanding of the mechanisms involved in the development of liver fibrosis and HCC.