Junwang Zhang, Xumei Kang, Ling Zhang, Hui-min Wang, Z. Deng
{"title":"非酒精性脂肪性肝炎17基因特征的鉴定及其与免疫细胞浸润的关系","authors":"Junwang Zhang, Xumei Kang, Ling Zhang, Hui-min Wang, Z. Deng","doi":"10.5812/HEPATMON.116366","DOIUrl":null,"url":null,"abstract":"Background: Non-alcoholic steatohepatitis (NASH) is a risk factor for hepatocellular carcinoma, but the understanding of the regulatory mechanisms driving NASH is not comprehensive. Objectives: We aimed to identify the potential markers of NASH and explore their relationship with immune cell populations. Methods: Five gene expression datasets for NASH were downloaded from the Gene Expression Omnibus and European Bioinformatics Institute (EBI) Array Express databases. Differentially expressed genes (DEGs) between NASH and controls were screened. Gene Ontology-Biological Process (GO-BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed for functional enrichment analysis of DEGs. Among the candidate genes selected from the protein-protein interaction (PPI) network and module analysis, DEG signatures were further identified using least absolute shrinkage and selection operator (LASSO) regression analysis. The Spearman correlation coefficient was calculated to assess the correlation between DEG signatures and immune cell abundance based on the CIBERSORT algorithm. Results: We screened 403 upregulated, and 158 downregulated DEGs for NASH, and they were mainly enriched in GO-BP, including the inflammatory response, innate immune response, signal transduction, and KEGG pathways, such as the pathways involved in cancer (e.g., the PI3K-Akt signaling pathway), and focal adhesion. We then screened 73 candidate genes from the PPI network and module analysis and finally identified 17 DEG signatures. By evaluating their relationship with immune cell populations, 12 DEG signatures were found to correlate with activated dendritic cells, resting dendritic cells, M2 macrophages, monocytes, neutrophils, and resting memory CD4 T cells, which were significantly different between the NASH and control tissues. Conclusions: We identified a 17-DEG-signature as a candidate biomarker for NASH and analyzed its relationship with immune infiltration in NASH.","PeriodicalId":12895,"journal":{"name":"Hepatitis Monthly","volume":" ","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of a 17-gene-signature in Non-alcoholic Steatohepatitis and Its Relationship with Immune Cell Infiltration\",\"authors\":\"Junwang Zhang, Xumei Kang, Ling Zhang, Hui-min Wang, Z. Deng\",\"doi\":\"10.5812/HEPATMON.116366\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: Non-alcoholic steatohepatitis (NASH) is a risk factor for hepatocellular carcinoma, but the understanding of the regulatory mechanisms driving NASH is not comprehensive. Objectives: We aimed to identify the potential markers of NASH and explore their relationship with immune cell populations. Methods: Five gene expression datasets for NASH were downloaded from the Gene Expression Omnibus and European Bioinformatics Institute (EBI) Array Express databases. Differentially expressed genes (DEGs) between NASH and controls were screened. Gene Ontology-Biological Process (GO-BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed for functional enrichment analysis of DEGs. Among the candidate genes selected from the protein-protein interaction (PPI) network and module analysis, DEG signatures were further identified using least absolute shrinkage and selection operator (LASSO) regression analysis. The Spearman correlation coefficient was calculated to assess the correlation between DEG signatures and immune cell abundance based on the CIBERSORT algorithm. Results: We screened 403 upregulated, and 158 downregulated DEGs for NASH, and they were mainly enriched in GO-BP, including the inflammatory response, innate immune response, signal transduction, and KEGG pathways, such as the pathways involved in cancer (e.g., the PI3K-Akt signaling pathway), and focal adhesion. We then screened 73 candidate genes from the PPI network and module analysis and finally identified 17 DEG signatures. By evaluating their relationship with immune cell populations, 12 DEG signatures were found to correlate with activated dendritic cells, resting dendritic cells, M2 macrophages, monocytes, neutrophils, and resting memory CD4 T cells, which were significantly different between the NASH and control tissues. Conclusions: We identified a 17-DEG-signature as a candidate biomarker for NASH and analyzed its relationship with immune infiltration in NASH.\",\"PeriodicalId\":12895,\"journal\":{\"name\":\"Hepatitis Monthly\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2021-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Hepatitis Monthly\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.5812/HEPATMON.116366\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"GASTROENTEROLOGY & HEPATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hepatitis Monthly","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.5812/HEPATMON.116366","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}
Identification of a 17-gene-signature in Non-alcoholic Steatohepatitis and Its Relationship with Immune Cell Infiltration
Background: Non-alcoholic steatohepatitis (NASH) is a risk factor for hepatocellular carcinoma, but the understanding of the regulatory mechanisms driving NASH is not comprehensive. Objectives: We aimed to identify the potential markers of NASH and explore their relationship with immune cell populations. Methods: Five gene expression datasets for NASH were downloaded from the Gene Expression Omnibus and European Bioinformatics Institute (EBI) Array Express databases. Differentially expressed genes (DEGs) between NASH and controls were screened. Gene Ontology-Biological Process (GO-BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed for functional enrichment analysis of DEGs. Among the candidate genes selected from the protein-protein interaction (PPI) network and module analysis, DEG signatures were further identified using least absolute shrinkage and selection operator (LASSO) regression analysis. The Spearman correlation coefficient was calculated to assess the correlation between DEG signatures and immune cell abundance based on the CIBERSORT algorithm. Results: We screened 403 upregulated, and 158 downregulated DEGs for NASH, and they were mainly enriched in GO-BP, including the inflammatory response, innate immune response, signal transduction, and KEGG pathways, such as the pathways involved in cancer (e.g., the PI3K-Akt signaling pathway), and focal adhesion. We then screened 73 candidate genes from the PPI network and module analysis and finally identified 17 DEG signatures. By evaluating their relationship with immune cell populations, 12 DEG signatures were found to correlate with activated dendritic cells, resting dendritic cells, M2 macrophages, monocytes, neutrophils, and resting memory CD4 T cells, which were significantly different between the NASH and control tissues. Conclusions: We identified a 17-DEG-signature as a candidate biomarker for NASH and analyzed its relationship with immune infiltration in NASH.
期刊介绍:
Hepatitis Monthly is a clinical journal which is informative to all practitioners like gastroenterologists, hepatologists and infectious disease specialists and internists. This authoritative clinical journal was founded by Professor Seyed-Moayed Alavian in 2002. The Journal context is devoted to the particular compilation of the latest worldwide and interdisciplinary approach and findings including original manuscripts, meta-analyses and reviews, health economic papers, debates and consensus statements of the clinical relevance of hepatological field especially liver diseases. In addition, consensus evidential reports not only highlight the new observations, original research, and results accompanied by innovative treatments and all the other relevant topics but also include highlighting disease mechanisms or important clinical observations and letters on articles published in the journal.