Shuyan Sheng, Bangjie Chen, Ruiyao Xu, Yanxun Han, Deshen Mao, Yuerong Chen, Conghan Li, Wenzhuo Su, Xinyang Hu, Qing Zhao, Scott Lowe, Yuting Huang, Wei Shao, Yong Yao
{"title":"日本血吸虫感染相关肝肝细胞癌的预后模型:通过初步生物实验加强联系。","authors":"Shuyan Sheng, Bangjie Chen, Ruiyao Xu, Yanxun Han, Deshen Mao, Yuerong Chen, Conghan Li, Wenzhuo Su, Xinyang Hu, Qing Zhao, Scott Lowe, Yuting Huang, Wei Shao, Yong Yao","doi":"10.1186/s13027-024-00569-4","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Numerous studies have shown that Schistosoma japonicum infection correlates with an increased risk of liver hepatocellular carcinoma (LIHC). However, data regarding the role of this infection in LIHC oncogenesis are scarce. This study aimed to investigate the potential mechanisms of hepatocarcinogenesis associated with Schistosoma japonicum infection.</p><p><strong>Methods: </strong>By examining chronic liver disease as a mediator, we identified the genes contributing to Schistosoma japonicum infection and LIHC. We selected 15 key differentially expressed genes (DEGs) using weighted gene co-expression network analysis (WGCNA) and random survival forest models. Consensus clustering revealed two subgroups with distinct prognoses. Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression identified six prognostic DEGs, forming an Schistosoma japonicum infection-associated signature for strong prognosis prediction. This signature, which is an independent LIHC risk factor, was significantly correlated with clinical variables. Four DEGs, including BMI1, were selected based on their protein expression levels in cancerous and normal tissues. We confirmed BMI1's role in LIHC using Schistosoma japonicum-infected mouse models and molecular experiments.</p><p><strong>Results: </strong>We identified a series of DEGs that mediate schistosomiasis, the parasitic disease caused by Schistosoma japonicum infection, and hepatocarcinogenesis, and constructed a suitable prognostic model. We analyzed the mechanisms by which these DEGs regulate disease and present the differences in prognosis between the different genotypes. Finally, we verified our findings using molecular biology experiments.</p><p><strong>Conclusion: </strong>Bioinformatics and molecular biology analyses confirmed a relationship between schistosomiasis and liver hepatocellular cancer. Furthermore, we validated the role of a potential oncoprotein factor that may be associated with infection and carcinogenesis. These findings enhance our understanding of Schistosoma japonicum infection's role in LIHC carcinogenesis.</p>","PeriodicalId":13568,"journal":{"name":"Infectious Agents and Cancer","volume":"19 1","pages":"10"},"PeriodicalIF":3.1000,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10956344/pdf/","citationCount":"0","resultStr":"{\"title\":\"A prognostic model for Schistosoma japonicum infection-associated liver hepatocellular carcinoma: strengthening the connection through initial biological experiments.\",\"authors\":\"Shuyan Sheng, Bangjie Chen, Ruiyao Xu, Yanxun Han, Deshen Mao, Yuerong Chen, Conghan Li, Wenzhuo Su, Xinyang Hu, Qing Zhao, Scott Lowe, Yuting Huang, Wei Shao, Yong Yao\",\"doi\":\"10.1186/s13027-024-00569-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Numerous studies have shown that Schistosoma japonicum infection correlates with an increased risk of liver hepatocellular carcinoma (LIHC). However, data regarding the role of this infection in LIHC oncogenesis are scarce. This study aimed to investigate the potential mechanisms of hepatocarcinogenesis associated with Schistosoma japonicum infection.</p><p><strong>Methods: </strong>By examining chronic liver disease as a mediator, we identified the genes contributing to Schistosoma japonicum infection and LIHC. We selected 15 key differentially expressed genes (DEGs) using weighted gene co-expression network analysis (WGCNA) and random survival forest models. Consensus clustering revealed two subgroups with distinct prognoses. Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression identified six prognostic DEGs, forming an Schistosoma japonicum infection-associated signature for strong prognosis prediction. This signature, which is an independent LIHC risk factor, was significantly correlated with clinical variables. Four DEGs, including BMI1, were selected based on their protein expression levels in cancerous and normal tissues. We confirmed BMI1's role in LIHC using Schistosoma japonicum-infected mouse models and molecular experiments.</p><p><strong>Results: </strong>We identified a series of DEGs that mediate schistosomiasis, the parasitic disease caused by Schistosoma japonicum infection, and hepatocarcinogenesis, and constructed a suitable prognostic model. We analyzed the mechanisms by which these DEGs regulate disease and present the differences in prognosis between the different genotypes. Finally, we verified our findings using molecular biology experiments.</p><p><strong>Conclusion: </strong>Bioinformatics and molecular biology analyses confirmed a relationship between schistosomiasis and liver hepatocellular cancer. Furthermore, we validated the role of a potential oncoprotein factor that may be associated with infection and carcinogenesis. These findings enhance our understanding of Schistosoma japonicum infection's role in LIHC carcinogenesis.</p>\",\"PeriodicalId\":13568,\"journal\":{\"name\":\"Infectious Agents and Cancer\",\"volume\":\"19 1\",\"pages\":\"10\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-03-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10956344/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Infectious Agents and Cancer\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s13027-024-00569-4\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"IMMUNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Infectious Agents and Cancer","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13027-024-00569-4","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
A prognostic model for Schistosoma japonicum infection-associated liver hepatocellular carcinoma: strengthening the connection through initial biological experiments.
Background: Numerous studies have shown that Schistosoma japonicum infection correlates with an increased risk of liver hepatocellular carcinoma (LIHC). However, data regarding the role of this infection in LIHC oncogenesis are scarce. This study aimed to investigate the potential mechanisms of hepatocarcinogenesis associated with Schistosoma japonicum infection.
Methods: By examining chronic liver disease as a mediator, we identified the genes contributing to Schistosoma japonicum infection and LIHC. We selected 15 key differentially expressed genes (DEGs) using weighted gene co-expression network analysis (WGCNA) and random survival forest models. Consensus clustering revealed two subgroups with distinct prognoses. Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression identified six prognostic DEGs, forming an Schistosoma japonicum infection-associated signature for strong prognosis prediction. This signature, which is an independent LIHC risk factor, was significantly correlated with clinical variables. Four DEGs, including BMI1, were selected based on their protein expression levels in cancerous and normal tissues. We confirmed BMI1's role in LIHC using Schistosoma japonicum-infected mouse models and molecular experiments.
Results: We identified a series of DEGs that mediate schistosomiasis, the parasitic disease caused by Schistosoma japonicum infection, and hepatocarcinogenesis, and constructed a suitable prognostic model. We analyzed the mechanisms by which these DEGs regulate disease and present the differences in prognosis between the different genotypes. Finally, we verified our findings using molecular biology experiments.
Conclusion: Bioinformatics and molecular biology analyses confirmed a relationship between schistosomiasis and liver hepatocellular cancer. Furthermore, we validated the role of a potential oncoprotein factor that may be associated with infection and carcinogenesis. These findings enhance our understanding of Schistosoma japonicum infection's role in LIHC carcinogenesis.
期刊介绍:
Infectious Agents and Cancer is an open access, peer-reviewed online journal that encompasses all aspects of basic, clinical, epidemiological and translational research providing an insight into the association between chronic infections and cancer.
The journal welcomes submissions in the pathogen-related cancer areas and other related topics, in particular:
• HPV and anogenital cancers, as well as head and neck cancers;
• EBV and Burkitt lymphoma;
• HCV/HBV and hepatocellular carcinoma as well as lymphoproliferative diseases;
• HHV8 and Kaposi sarcoma;
• HTLV and leukemia;
• Cancers in Low- and Middle-income countries.
The link between infection and cancer has become well established over the past 50 years, and infection-associated cancer contribute up to 16% of cancers in developed countries and 33% in less developed countries.
Preventive vaccines have been developed for only two cancer-causing viruses, highlighting both the opportunity to prevent infection-associated cancers by vaccination and the gaps that remain before vaccines can be developed for other cancer-causing agents. These gaps are due to incomplete understanding of the basic biology, natural history, epidemiology of many of the pathogens that cause cancer, the mechanisms they exploit to cause cancer, and how to interrupt progression to cancer in human populations. Early diagnosis or identification of lesions at high risk of progression represent the current most critical research area of the field supported by recent advances in genomics and proteomics technologies.