Liping Ren, Xianrun Pan, Lin Ning, Di Gong, Jian Huang, Kejun Deng, Lei Xie, Yang Zhang
{"title":"肝细胞癌预后缺氧相关基因联合模型的构建","authors":"Liping Ren, Xianrun Pan, Lin Ning, Di Gong, Jian Huang, Kejun Deng, Lei Xie, Yang Zhang","doi":"10.2174/1573409919666221223123610","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Hepatocellular carcinoma (HCC) is the most common liver malignancy where tumorigenesis and metastasis are believed to be tied to the hallmarks of hypoxia and tumor microenvironment (TME).</p><p><strong>Methods: </strong>In this study, to investigate the relationships among hypoxia, TME, and HCC prognosis, we collected two independent datasets from a public database (TCGA-LIHC for identification, GSE14520 for validation) and identified the hypoxia-related differentially expressed genes (DEGs) from the TCGA data, and the univariable Cox regression and lasso regression analyses were performed to construct the prognosis model. An HCC prognosis model with 4 hypoxiarelated DEGs (\"NDRG1\", \"ENO1\", \"SERPINE1\", \"ANXA2\") was constructed, and high- and low-risk groups of HCC were established by the median of the model risk score.</p><p><strong>Results: </strong>The survival analysis revealed significant differences between the two groups in both datasets, with the results of the AUC of the ROC curve of 1, 3, and 5 years in two datasets indicating the robustness of the prognosis model. Meanwhile, for the TCGA-LIHC data, the immune characteristics between the two groups revealed that the low-risk group presented higher levels of activated NK cells, monocytes, and M2 macrophages, and 7 immune checkpoint genes were found upregulated in the high-risk group. Additionally, the two groups have no difference in molecular characteristics (tumor mutational burden, TMB). The proportion of recurrence was higher in the high-risk group, and the correlation between the recurrence month and risk score was negative, indicating high-risk correlates with a short recurrence month.</p><p><strong>Conclusion: </strong>In summary, this study shows the association among hypoxic signals, TME, and HCC prognosis and may help reveal potential regulatory mechanisms between hypoxia, tumorigenesis, and metastasis in HCC. The hypoxia-related model demonstrated the potential to be a predictor and drug target of prognosis.</p>","PeriodicalId":10886,"journal":{"name":"Current computer-aided drug design","volume":"19 2","pages":"150-161"},"PeriodicalIF":1.5000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Construction of a Combined Hypoxia-related Genes Model for Hepatocellular Carcinoma Prognosis.\",\"authors\":\"Liping Ren, Xianrun Pan, Lin Ning, Di Gong, Jian Huang, Kejun Deng, Lei Xie, Yang Zhang\",\"doi\":\"10.2174/1573409919666221223123610\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Hepatocellular carcinoma (HCC) is the most common liver malignancy where tumorigenesis and metastasis are believed to be tied to the hallmarks of hypoxia and tumor microenvironment (TME).</p><p><strong>Methods: </strong>In this study, to investigate the relationships among hypoxia, TME, and HCC prognosis, we collected two independent datasets from a public database (TCGA-LIHC for identification, GSE14520 for validation) and identified the hypoxia-related differentially expressed genes (DEGs) from the TCGA data, and the univariable Cox regression and lasso regression analyses were performed to construct the prognosis model. An HCC prognosis model with 4 hypoxiarelated DEGs (\\\"NDRG1\\\", \\\"ENO1\\\", \\\"SERPINE1\\\", \\\"ANXA2\\\") was constructed, and high- and low-risk groups of HCC were established by the median of the model risk score.</p><p><strong>Results: </strong>The survival analysis revealed significant differences between the two groups in both datasets, with the results of the AUC of the ROC curve of 1, 3, and 5 years in two datasets indicating the robustness of the prognosis model. Meanwhile, for the TCGA-LIHC data, the immune characteristics between the two groups revealed that the low-risk group presented higher levels of activated NK cells, monocytes, and M2 macrophages, and 7 immune checkpoint genes were found upregulated in the high-risk group. Additionally, the two groups have no difference in molecular characteristics (tumor mutational burden, TMB). The proportion of recurrence was higher in the high-risk group, and the correlation between the recurrence month and risk score was negative, indicating high-risk correlates with a short recurrence month.</p><p><strong>Conclusion: </strong>In summary, this study shows the association among hypoxic signals, TME, and HCC prognosis and may help reveal potential regulatory mechanisms between hypoxia, tumorigenesis, and metastasis in HCC. The hypoxia-related model demonstrated the potential to be a predictor and drug target of prognosis.</p>\",\"PeriodicalId\":10886,\"journal\":{\"name\":\"Current computer-aided drug design\",\"volume\":\"19 2\",\"pages\":\"150-161\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current computer-aided drug design\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2174/1573409919666221223123610\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"CHEMISTRY, MEDICINAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current computer-aided drug design","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2174/1573409919666221223123610","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
Construction of a Combined Hypoxia-related Genes Model for Hepatocellular Carcinoma Prognosis.
Background: Hepatocellular carcinoma (HCC) is the most common liver malignancy where tumorigenesis and metastasis are believed to be tied to the hallmarks of hypoxia and tumor microenvironment (TME).
Methods: In this study, to investigate the relationships among hypoxia, TME, and HCC prognosis, we collected two independent datasets from a public database (TCGA-LIHC for identification, GSE14520 for validation) and identified the hypoxia-related differentially expressed genes (DEGs) from the TCGA data, and the univariable Cox regression and lasso regression analyses were performed to construct the prognosis model. An HCC prognosis model with 4 hypoxiarelated DEGs ("NDRG1", "ENO1", "SERPINE1", "ANXA2") was constructed, and high- and low-risk groups of HCC were established by the median of the model risk score.
Results: The survival analysis revealed significant differences between the two groups in both datasets, with the results of the AUC of the ROC curve of 1, 3, and 5 years in two datasets indicating the robustness of the prognosis model. Meanwhile, for the TCGA-LIHC data, the immune characteristics between the two groups revealed that the low-risk group presented higher levels of activated NK cells, monocytes, and M2 macrophages, and 7 immune checkpoint genes were found upregulated in the high-risk group. Additionally, the two groups have no difference in molecular characteristics (tumor mutational burden, TMB). The proportion of recurrence was higher in the high-risk group, and the correlation between the recurrence month and risk score was negative, indicating high-risk correlates with a short recurrence month.
Conclusion: In summary, this study shows the association among hypoxic signals, TME, and HCC prognosis and may help reveal potential regulatory mechanisms between hypoxia, tumorigenesis, and metastasis in HCC. The hypoxia-related model demonstrated the potential to be a predictor and drug target of prognosis.
期刊介绍:
Aims & Scope
Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design.
Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews, original research articles and letter articles written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, theoretical chemistry; computational chemistry; computer and molecular graphics; molecular modeling; protein engineering; drug design; expert systems; general structure-property relationships; molecular dynamics; chemical database development and usage etc., providing excellent rationales for drug development.