Z Wang1, Z Zhao1, Y Xia1, Z Cai1, C Wang1, Y Shen1, R Liu1, H Qin1, J Jia2, G Yuan3. 1. Department of Endocrinology, Affiliated Hospital of Jiangsu University, Zhenjiang, 212001, Jiangsu, China. 2. Department of Endocrinology, Affiliated Hospital of Jiangsu University, Zhenjiang, 212001, Jiangsu, China. xibeizijj@aliyun.com. 3. Department of Endocrinology, Affiliated Hospital of Jiangsu University, Zhenjiang, 212001, Jiangsu, China. yuanguoyue@ujs.edu.cn.
Abstract
PURPOSE: Fibrosis is the only histological feature reflecting the severity and prognosis of nonalcoholic steatohepatitis (NASH). We aim to explore novel genes associated with fibrosis progression in NASH. METHODS: Two human RNA-seq datasets were downloaded from the public database. Weighted gene co-expression network analysis (WGCNA) was used to identify their co-expressed modules and further bioinformatics analysis was performed to identify hub genes within the modules. Finally, based on two single-cell RNA-seq datasets from mice and one microarray dataset from human, we further observed the expression of hub genes in different cell clusters and liver tissues. RESULTS: 7 hub genes (SPP1, PROM1, SOX9, EPCAM, THY1, CD34 and MCAM) associated with fibrosis progression were identified. Single-cell RNA-seq analysis revealed that those hub genes were expressed by different cell clusters such as cholangiocytes, natural killer (NK) cells, and hepatic stellate cells (HSCs). We also found that SPP1 and CD34 serve as markers of different HSCs clusters, which are associated with inflammatory response and fibrogenesis, respectively. Further study suggested that SPP1, SOX9, MCAM and THY1 might be related to NASH-associated hepatocellular carcinoma (HCC). Receiver operating characteristic (ROC) analysis showed that the high expression of these genes could well predict the occurrence of HCC. At the same time, there were significant differences in metabolism-related pathway changes between different HCC subtypes, and SOX9 may be involved in these changes. CONCLUSIONS: The present study identified novel genes associated with NASH fibrosis and explored their effects on fibrosis from a single-cell perspective that might provide new ideas for the early diagnosis, monitoring, evaluation, and prediction of fibrosis progression in NASH.
PURPOSE: Fibrosis is the only histological feature reflecting the severity and prognosis of nonalcoholic steatohepatitis (NASH). We aim to explore novel genes associated with fibrosis progression in NASH. METHODS: Two human RNA-seq datasets were downloaded from the public database. Weighted gene co-expression network analysis (WGCNA) was used to identify their co-expressed modules and further bioinformatics analysis was performed to identify hub genes within the modules. Finally, based on two single-cell RNA-seq datasets from mice and one microarray dataset from human, we further observed the expression of hub genes in different cell clusters and liver tissues. RESULTS: 7 hub genes (SPP1, PROM1, SOX9, EPCAM, THY1, CD34 and MCAM) associated with fibrosis progression were identified. Single-cell RNA-seq analysis revealed that those hub genes were expressed by different cell clusters such as cholangiocytes, natural killer (NK) cells, and hepatic stellate cells (HSCs). We also found that SPP1 and CD34 serve as markers of different HSCs clusters, which are associated with inflammatory response and fibrogenesis, respectively. Further study suggested that SPP1, SOX9, MCAM and THY1 might be related to NASH-associated hepatocellular carcinoma (HCC). Receiver operating characteristic (ROC) analysis showed that the high expression of these genes could well predict the occurrence of HCC. At the same time, there were significant differences in metabolism-related pathway changes between different HCC subtypes, and SOX9 may be involved in these changes. CONCLUSIONS: The present study identified novel genes associated with NASH fibrosis and explored their effects on fibrosis from a single-cell perspective that might provide new ideas for the early diagnosis, monitoring, evaluation, and prediction of fibrosis progression in NASH.
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