{"title":"通过生物信息学探索非酒精性脂肪性肝炎和肝细胞癌的共同遗传特征和分子机制。","authors":"ChengLong Tian, Zheng Li, QinLong Liu","doi":"10.2174/0113862073323011240912072514","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Hepatocellular Carcinoma (HCC) is one of the most common malignant tumors in the world, characterized by high incidence, high malignancy, and low survival rate. Currently, 1/4 of adults in the world suffer from Non-Alcoholic Fatty Liver Disease (NAFLD), with an incidence rate of 27% in Asia.</p><p><strong>Methods: </strong>We used TCGA and GEO public database data sets to conduct weighted gene coexpression network analysis to identify relevant gene modules, defined the intersection of tumorigenesis-related modules and NASH development-related modules as shared genes, and then used single-factor Cox, LASSO, and multivariate Cox regression analysis screened out core shared genes and verified their prognostic value. We further investigated the relationship between core shared genes and immune infiltration, tumor mutational load, and drug sensitivity. Finally, RT-qPCR was used to verify its mRNA expression in different cell lines.</p><p><strong>Results: </strong>We identified Karyopherin α 2 (KPNA2) as the core shared gene between NASH and HCC. Patients were divided into low-risk groups and high-risk groups based on the expression of KPNA2. The prognosis of the low-risk group was significantly better than that of the highrisk group. Furthermore, we found significant differences in tumor immune cell infiltration, somatic mutations, microsatellite instability, and drug sensitivity between different expression groups.</p><p><strong>Conclusion: </strong>There are very few studies on the molecular mechanism of the relationship between NAFLD and HCC. Our study demonstrates that KPNA2 is a potential therapeutic target and immune-related biomarker for patients with NAFLD and HCC.</p>","PeriodicalId":10491,"journal":{"name":"Combinatorial chemistry & high throughput screening","volume":" ","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exploring Shared Genetic Features and Molecular Mechanisms between Non-Alcoholic Steatohepatitis and Hepatocellular Carcinoma through Bioinformatics.\",\"authors\":\"ChengLong Tian, Zheng Li, QinLong Liu\",\"doi\":\"10.2174/0113862073323011240912072514\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Hepatocellular Carcinoma (HCC) is one of the most common malignant tumors in the world, characterized by high incidence, high malignancy, and low survival rate. Currently, 1/4 of adults in the world suffer from Non-Alcoholic Fatty Liver Disease (NAFLD), with an incidence rate of 27% in Asia.</p><p><strong>Methods: </strong>We used TCGA and GEO public database data sets to conduct weighted gene coexpression network analysis to identify relevant gene modules, defined the intersection of tumorigenesis-related modules and NASH development-related modules as shared genes, and then used single-factor Cox, LASSO, and multivariate Cox regression analysis screened out core shared genes and verified their prognostic value. We further investigated the relationship between core shared genes and immune infiltration, tumor mutational load, and drug sensitivity. Finally, RT-qPCR was used to verify its mRNA expression in different cell lines.</p><p><strong>Results: </strong>We identified Karyopherin α 2 (KPNA2) as the core shared gene between NASH and HCC. Patients were divided into low-risk groups and high-risk groups based on the expression of KPNA2. The prognosis of the low-risk group was significantly better than that of the highrisk group. Furthermore, we found significant differences in tumor immune cell infiltration, somatic mutations, microsatellite instability, and drug sensitivity between different expression groups.</p><p><strong>Conclusion: </strong>There are very few studies on the molecular mechanism of the relationship between NAFLD and HCC. Our study demonstrates that KPNA2 is a potential therapeutic target and immune-related biomarker for patients with NAFLD and HCC.</p>\",\"PeriodicalId\":10491,\"journal\":{\"name\":\"Combinatorial chemistry & high throughput screening\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Combinatorial chemistry & high throughput screening\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2174/0113862073323011240912072514\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Combinatorial chemistry & high throughput screening","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2174/0113862073323011240912072514","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
Exploring Shared Genetic Features and Molecular Mechanisms between Non-Alcoholic Steatohepatitis and Hepatocellular Carcinoma through Bioinformatics.
Background: Hepatocellular Carcinoma (HCC) is one of the most common malignant tumors in the world, characterized by high incidence, high malignancy, and low survival rate. Currently, 1/4 of adults in the world suffer from Non-Alcoholic Fatty Liver Disease (NAFLD), with an incidence rate of 27% in Asia.
Methods: We used TCGA and GEO public database data sets to conduct weighted gene coexpression network analysis to identify relevant gene modules, defined the intersection of tumorigenesis-related modules and NASH development-related modules as shared genes, and then used single-factor Cox, LASSO, and multivariate Cox regression analysis screened out core shared genes and verified their prognostic value. We further investigated the relationship between core shared genes and immune infiltration, tumor mutational load, and drug sensitivity. Finally, RT-qPCR was used to verify its mRNA expression in different cell lines.
Results: We identified Karyopherin α 2 (KPNA2) as the core shared gene between NASH and HCC. Patients were divided into low-risk groups and high-risk groups based on the expression of KPNA2. The prognosis of the low-risk group was significantly better than that of the highrisk group. Furthermore, we found significant differences in tumor immune cell infiltration, somatic mutations, microsatellite instability, and drug sensitivity between different expression groups.
Conclusion: There are very few studies on the molecular mechanism of the relationship between NAFLD and HCC. Our study demonstrates that KPNA2 is a potential therapeutic target and immune-related biomarker for patients with NAFLD and HCC.
期刊介绍:
Combinatorial Chemistry & High Throughput Screening (CCHTS) publishes full length original research articles and reviews/mini-reviews dealing with various topics related to chemical biology (High Throughput Screening, Combinatorial Chemistry, Chemoinformatics, Laboratory Automation and Compound management) in advancing drug discovery research. Original research articles and reviews in the following areas are of special interest to the readers of this journal:
Target identification and validation
Assay design, development, miniaturization and comparison
High throughput/high content/in silico screening and associated technologies
Label-free detection technologies and applications
Stem cell technologies
Biomarkers
ADMET/PK/PD methodologies and screening
Probe discovery and development, hit to lead optimization
Combinatorial chemistry (e.g. small molecules, peptide, nucleic acid or phage display libraries)
Chemical library design and chemical diversity
Chemo/bio-informatics, data mining
Compound management
Pharmacognosy
Natural Products Research (Chemistry, Biology and Pharmacology of Natural Products)
Natural Product Analytical Studies
Bipharmaceutical studies of Natural products
Drug repurposing
Data management and statistical analysis
Laboratory automation, robotics, microfluidics, signal detection technologies
Current & Future Institutional Research Profile
Technology transfer, legal and licensing issues
Patents.