Clinical and Translational Research
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Oncol. Jul 15, 2022; 14(7): 1265-1280
Published online Jul 15, 2022. doi: 10.4251/wjgo.v14.i7.1265
Differences of core genes in liver fibrosis and hepatocellular carcinoma: Evidence from integrated bioinformatics and immunohistochemical analysis
Yue Li, Shou-Li Yuan, Jing-Ya Yin, Kun Yang, Xin-Gang Zhou, Wen Xie, Qi Wang
Yue Li, Kun Yang, Xin-Gang Zhou, Department of Pathology, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
Yue Li, Beijing Key Laboratory of Emerging Infectious Diseases, Beijing 100015, China
Shou-Li Yuan, Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Beijing 100101, China
Jing-Ya Yin, Wen Xie, Qi Wang, Center of Liver Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
Author contributions: Li Y and Yuan SL contributed equally to this work; Wang Q and Xie W designed the research and were co-corresponding authors; Yuan SL, Li Y, Yin JY, Yang K and Zhou XG performed the experiments; Yuan SL and Li Y analyzed the data; Yuan SL, Li Y and Wang Q wrote the manuscript; Yuan SL provided vital reagents and analytical tools; all authors read and approved the final manuscript.
Supported by the Beijing Natural Science Foundation, No. 7222097; Beijing Hospitals Authority the Digestive Medical Coordinated Development Center, No. XXZ0401; National Natural Science Foundation of China, No. 82000555 and No. 81900547; and Beijing Municipal Science and Technology Commission, No. D171100003117005.
Institutional review board statement: The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki as reflected in a priori approval by the Ethics Committee of Beijing Ditan Hospital No. 2021-034-01.
Informed consent statement: Patients were not required to give informed consent to the study because the analysis used anonymous clinical data and liver tissue samples.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: Publicly available datasets were analyzed in this study, which can be found here: GSE14323, GSE36411 and GSE89377. Technical appendix, statistical code, and data set available from the corresponding author at No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See:
Corresponding author: Qi Wang, MD, PhD, Reader (Associate Professor), Center of Liver Diseases, Beijing Ditan Hospital, Capital Medical University, No. 8 East Jingshun Street, Chaoyang District, Beijing 100015, China.
Received: January 25, 2022
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
Research background

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.

Research motivation

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.

Research objectives

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.

Research methods

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.

Research results

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.

Research conclusions

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.

Research perspectives

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.