Identification and validation of potential diagnostic signature and immune cell infiltration for NAFLD based on cuproptosis-related genes by bioinformatics analysis and machine learning
Background and aimsCuproptosis has been identified as a key player in the development of several diseases. In this study, we investigate the potential role of cuproptosis-related genes in the pathogenesis of nonalcoholic fatty liver disease (NAFLD).MethodThe gene expression profiles of NAFLD were ob...
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Frontiers Media S.A.
2023-09-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2023.1251750/full |
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| author | Guoqing Ouyang Guoqing Ouyang Guoqing Ouyang Guoqing Ouyang Zhan Wu Zhan Wu Zhan Wu Zhipeng Liu Zhipeng Liu Zhipeng Liu Guandong Pan Guandong Pan Yong Wang Yong Wang Yong Wang Jing Liu Jing Liu Jing Liu Jixu Guo Jixu Guo Jixu Guo Tao Liu Guozhen Huang Guozhen Huang Guozhen Huang Yonglian Zeng Yonglian Zeng Yonglian Zeng Zaiwa Wei Zaiwa Wei Zaiwa Wei Songqing He Songqing He Songqing He Guandou Yuan Guandou Yuan Guandou Yuan |
| author_facet | Guoqing Ouyang Guoqing Ouyang Guoqing Ouyang Guoqing Ouyang Zhan Wu Zhan Wu Zhan Wu Zhipeng Liu Zhipeng Liu Zhipeng Liu Guandong Pan Guandong Pan Yong Wang Yong Wang Yong Wang Jing Liu Jing Liu Jing Liu Jixu Guo Jixu Guo Jixu Guo Tao Liu Guozhen Huang Guozhen Huang Guozhen Huang Yonglian Zeng Yonglian Zeng Yonglian Zeng Zaiwa Wei Zaiwa Wei Zaiwa Wei Songqing He Songqing He Songqing He Guandou Yuan Guandou Yuan Guandou Yuan |
| author_sort | Guoqing Ouyang |
| collection | DOAJ |
| description | Background and aimsCuproptosis has been identified as a key player in the development of several diseases. In this study, we investigate the potential role of cuproptosis-related genes in the pathogenesis of nonalcoholic fatty liver disease (NAFLD).MethodThe gene expression profiles of NAFLD were obtained from the Gene Expression Omnibus database. Differential expression of cuproptosis-related genes (CRGs) were determined between NAFLD and normal tissues. Protein–protein interaction, correlation, and function enrichment analyses were performed. Machine learning was used to identify hub genes. Immune infiltration was analyzed in both NAFLD patients and controls. Quantitative real-time PCR was employed to validate the expression of hub genes.ResultsFour datasets containing 115 NAFLD and 106 control samples were included for bioinformatics analysis. Three hub CRGs (NFE2L2, DLD, and POLD1) were identified through the intersection of three machine learning algorithms. The receiver operating characteristic curve was plotted based on these three marker genes, and the area under the curve (AUC) value was 0.704. In the external GSE135251 dataset, the AUC value of the three key genes was as high as 0.970. Further nomogram, decision curve, calibration curve analyses also confirmed the diagnostic predictive efficacy. Gene set enrichment analysis and gene set variation analysis showed these three marker genes involved in multiple pathways that are related to the progression of NAFLD. CIBERSORT and single-sample gene set enrichment analysis indicated that their expression levels in macrophages, mast cells, NK cells, Treg cells, resting dendritic cells, and tumor-infiltrating lymphocytes were higher in NAFLD compared with control liver samples. The ceRNA network demonstrated a complex regulatory relationship between the three hub genes. The mRNA level of these hub genes were further confirmed in a mouse NAFLD liver samples.ConclusionOur study comprehensively demonstrated the relationship between NAFLD and cuproptosis, developed a promising diagnostic model, and provided potential targets for NAFLD treatment and new insights for exploring the mechanism for NAFLD. |
| first_indexed | 2024-03-11T21:30:36Z |
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| id | doaj.art-33a8ca2f690a45d8a000d711bfd87120 |
| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-03-11T21:30:36Z |
| publishDate | 2023-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj.art-33a8ca2f690a45d8a000d711bfd871202023-09-27T09:31:26ZengFrontiers Media S.A.Frontiers in Immunology1664-32242023-09-011410.3389/fimmu.2023.12517501251750Identification and validation of potential diagnostic signature and immune cell infiltration for NAFLD based on cuproptosis-related genes by bioinformatics analysis and machine learningGuoqing Ouyang0Guoqing Ouyang1Guoqing Ouyang2Guoqing Ouyang3Zhan Wu4Zhan Wu5Zhan Wu6Zhipeng Liu7Zhipeng Liu8Zhipeng Liu9Guandong Pan10Guandong Pan11Yong Wang12Yong Wang13Yong Wang14Jing Liu15Jing Liu16Jing Liu17Jixu Guo18Jixu Guo19Jixu Guo20Tao Liu21Guozhen Huang22Guozhen Huang23Guozhen Huang24Yonglian Zeng25Yonglian Zeng26Yonglian Zeng27Zaiwa Wei28Zaiwa Wei29Zaiwa Wei30Songqing He31Songqing He32Songqing He33Guandou Yuan34Guandou Yuan35Guandou Yuan36Division of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, ChinaKey Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning, Guangxi, ChinaGuangxi Key Laboratory of Immunology and Metabolism for Liver Diseases, Guangxi Medical University, Nanning, Guangxi, ChinaLiuzhou Key Laboratory of Liver Cancer Research, Liuzhou People’s Hospital, Liuzhou, Guangxi, ChinaDivision of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, ChinaKey Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning, Guangxi, ChinaGuangxi Key Laboratory of Immunology and Metabolism for Liver Diseases, Guangxi Medical University, Nanning, Guangxi, ChinaDivision of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, ChinaKey Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning, Guangxi, ChinaGuangxi Key Laboratory of Immunology and Metabolism for Liver Diseases, Guangxi Medical University, Nanning, Guangxi, ChinaLiuzhou Key Laboratory of Liver Cancer Research, Liuzhou People’s Hospital, Liuzhou, Guangxi, ChinaLiuzhou Hepatobiliary and Pancreatic Diseases Precision Diagnosis Research Center of Engineering Technology, Liuzhou People’s Hospital by Liuzhou Science and Technology Bureau, Liuzhou, Guangxi, ChinaDivision of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, ChinaKey Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning, Guangxi, ChinaGuangxi Key Laboratory of Immunology and Metabolism for Liver Diseases, Guangxi Medical University, Nanning, Guangxi, ChinaDivision of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, ChinaKey Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning, Guangxi, ChinaGuangxi Key Laboratory of Immunology and Metabolism for Liver Diseases, Guangxi Medical University, Nanning, Guangxi, ChinaDivision of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, ChinaKey Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning, Guangxi, ChinaGuangxi Key Laboratory of Immunology and Metabolism for Liver Diseases, Guangxi Medical University, Nanning, Guangxi, ChinaDepartment of General Surgery, Luzhai People’s Hospital, Liuzhou, Guangxi, ChinaDivision of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, ChinaKey Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning, Guangxi, ChinaGuangxi Key Laboratory of Immunology and Metabolism for Liver Diseases, Guangxi Medical University, Nanning, Guangxi, ChinaDivision of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, ChinaKey Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning, Guangxi, ChinaGuangxi Key Laboratory of Immunology and Metabolism for Liver Diseases, Guangxi Medical University, Nanning, Guangxi, ChinaDivision of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, ChinaKey Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning, Guangxi, ChinaGuangxi Key Laboratory of Immunology and Metabolism for Liver Diseases, Guangxi Medical University, Nanning, Guangxi, ChinaDivision of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, ChinaKey Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning, Guangxi, ChinaGuangxi Key Laboratory of Immunology and Metabolism for Liver Diseases, Guangxi Medical University, Nanning, Guangxi, ChinaDivision of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, ChinaKey Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning, Guangxi, ChinaGuangxi Key Laboratory of Immunology and Metabolism for Liver Diseases, Guangxi Medical University, Nanning, Guangxi, ChinaBackground and aimsCuproptosis has been identified as a key player in the development of several diseases. In this study, we investigate the potential role of cuproptosis-related genes in the pathogenesis of nonalcoholic fatty liver disease (NAFLD).MethodThe gene expression profiles of NAFLD were obtained from the Gene Expression Omnibus database. Differential expression of cuproptosis-related genes (CRGs) were determined between NAFLD and normal tissues. Protein–protein interaction, correlation, and function enrichment analyses were performed. Machine learning was used to identify hub genes. Immune infiltration was analyzed in both NAFLD patients and controls. Quantitative real-time PCR was employed to validate the expression of hub genes.ResultsFour datasets containing 115 NAFLD and 106 control samples were included for bioinformatics analysis. Three hub CRGs (NFE2L2, DLD, and POLD1) were identified through the intersection of three machine learning algorithms. The receiver operating characteristic curve was plotted based on these three marker genes, and the area under the curve (AUC) value was 0.704. In the external GSE135251 dataset, the AUC value of the three key genes was as high as 0.970. Further nomogram, decision curve, calibration curve analyses also confirmed the diagnostic predictive efficacy. Gene set enrichment analysis and gene set variation analysis showed these three marker genes involved in multiple pathways that are related to the progression of NAFLD. CIBERSORT and single-sample gene set enrichment analysis indicated that their expression levels in macrophages, mast cells, NK cells, Treg cells, resting dendritic cells, and tumor-infiltrating lymphocytes were higher in NAFLD compared with control liver samples. The ceRNA network demonstrated a complex regulatory relationship between the three hub genes. The mRNA level of these hub genes were further confirmed in a mouse NAFLD liver samples.ConclusionOur study comprehensively demonstrated the relationship between NAFLD and cuproptosis, developed a promising diagnostic model, and provided potential targets for NAFLD treatment and new insights for exploring the mechanism for NAFLD.https://www.frontiersin.org/articles/10.3389/fimmu.2023.1251750/fullnonalcoholic fatty liver diseasecuproptosisimmune infiltrationmachine learningimmune microenvironment |
| spellingShingle | Guoqing Ouyang Guoqing Ouyang Guoqing Ouyang Guoqing Ouyang Zhan Wu Zhan Wu Zhan Wu Zhipeng Liu Zhipeng Liu Zhipeng Liu Guandong Pan Guandong Pan Yong Wang Yong Wang Yong Wang Jing Liu Jing Liu Jing Liu Jixu Guo Jixu Guo Jixu Guo Tao Liu Guozhen Huang Guozhen Huang Guozhen Huang Yonglian Zeng Yonglian Zeng Yonglian Zeng Zaiwa Wei Zaiwa Wei Zaiwa Wei Songqing He Songqing He Songqing He Guandou Yuan Guandou Yuan Guandou Yuan Identification and validation of potential diagnostic signature and immune cell infiltration for NAFLD based on cuproptosis-related genes by bioinformatics analysis and machine learning Frontiers in Immunology nonalcoholic fatty liver disease cuproptosis immune infiltration machine learning immune microenvironment |
| title | Identification and validation of potential diagnostic signature and immune cell infiltration for NAFLD based on cuproptosis-related genes by bioinformatics analysis and machine learning |
| title_full | Identification and validation of potential diagnostic signature and immune cell infiltration for NAFLD based on cuproptosis-related genes by bioinformatics analysis and machine learning |
| title_fullStr | Identification and validation of potential diagnostic signature and immune cell infiltration for NAFLD based on cuproptosis-related genes by bioinformatics analysis and machine learning |
| title_full_unstemmed | Identification and validation of potential diagnostic signature and immune cell infiltration for NAFLD based on cuproptosis-related genes by bioinformatics analysis and machine learning |
| title_short | Identification and validation of potential diagnostic signature and immune cell infiltration for NAFLD based on cuproptosis-related genes by bioinformatics analysis and machine learning |
| title_sort | identification and validation of potential diagnostic signature and immune cell infiltration for nafld based on cuproptosis related genes by bioinformatics analysis and machine learning |
| topic | nonalcoholic fatty liver disease cuproptosis immune infiltration machine learning immune microenvironment |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2023.1251750/full |
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