{"title":"基于孟德尔随机化和机器学习的三级淋巴结构相关基因特征与 HCC 的遗传关联及预后模型的构建。","authors":"Lei Pu, Xiaoyan Zhang, Cheng Pu, Jiacheng Zhou, Jianyue Li, Xiaorong Wang, Chenpeng Xi, Chunyuan Zhang","doi":"10.1016/j.intimp.2024.113594","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Tertiary lymphoid structures (TLS) are formed in numerous cancer types. However, their value and significance in hepatocellular carcinoma (HCC) is unclear.</p><p><strong>Methods: </strong>We performed differential genes expression analysis of TLS-related Genes (TLSG) based on The Cancer Genome Atlas (TCGA) database, and performed Mendelian randomization (MR) analysis using expression quantitative trait loci, and then took their intersecting genes. A TLSG prognostic signature (TLSGPS)-based risk score was constructed using Least Absolute Shrinkage and Selection Operator (LASSO), univariate and multivariate COX regression analysis, and survival analysis was then performed. We used the International Cancer Genome Consortium for outside validation. We also performed biological function, tumor mutational burden, immune infiltration, single-cell analysis, CeRNA and drug sensitivity analysis based on TLSGPS.</p><p><strong>Results: </strong>Three TLSGs (HM13, CSTB, CDCA7L) were identified to construct the TLSGPS, which showed good predictive ability and outperformed most prognostic signatures. MR suggested that HM13 (OR = 0.9997, 95 %CI: 0.9994-0.9999, P = 0.014) and CSTB (OR = 0.9997, 95 %CI: 0.9995-0.9999, P = 0.048) were negatively correlated with the risk of HCC onset, while CDCA7L (OR = 1.0004, 1.0001-1.0007, P = 0.0161) was the opposite. The differences in biological functions between the TLSGPS-based high-risk group (HRG) and low-risk group (LRG) involved cell proliferation, differentiation, and drug metabolism. HRG plus high mutations exhibited extremely poor survival. HRG had higher abundance of immune cell-oncogenic phenotypes, higher immune escape ability, and greater sensitivity to Afatinib, Dasatinib, and Gefitinib.</p><p><strong>Conclusion: </strong>3 TLSGs identified by machine learning and MR can predict the onset, prognosis and clinical treatment of HCC patients, and had significant genetic association with HCC.</p>","PeriodicalId":13859,"journal":{"name":"International immunopharmacology","volume":"144 ","pages":"113594"},"PeriodicalIF":4.8000,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Genetic association of tertiary lymphoid structure-related gene signatures with HCC based on Mendelian randomization and machine learning and construction of prognosis model.\",\"authors\":\"Lei Pu, Xiaoyan Zhang, Cheng Pu, Jiacheng Zhou, Jianyue Li, Xiaorong Wang, Chenpeng Xi, Chunyuan Zhang\",\"doi\":\"10.1016/j.intimp.2024.113594\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Tertiary lymphoid structures (TLS) are formed in numerous cancer types. However, their value and significance in hepatocellular carcinoma (HCC) is unclear.</p><p><strong>Methods: </strong>We performed differential genes expression analysis of TLS-related Genes (TLSG) based on The Cancer Genome Atlas (TCGA) database, and performed Mendelian randomization (MR) analysis using expression quantitative trait loci, and then took their intersecting genes. A TLSG prognostic signature (TLSGPS)-based risk score was constructed using Least Absolute Shrinkage and Selection Operator (LASSO), univariate and multivariate COX regression analysis, and survival analysis was then performed. We used the International Cancer Genome Consortium for outside validation. We also performed biological function, tumor mutational burden, immune infiltration, single-cell analysis, CeRNA and drug sensitivity analysis based on TLSGPS.</p><p><strong>Results: </strong>Three TLSGs (HM13, CSTB, CDCA7L) were identified to construct the TLSGPS, which showed good predictive ability and outperformed most prognostic signatures. MR suggested that HM13 (OR = 0.9997, 95 %CI: 0.9994-0.9999, P = 0.014) and CSTB (OR = 0.9997, 95 %CI: 0.9995-0.9999, P = 0.048) were negatively correlated with the risk of HCC onset, while CDCA7L (OR = 1.0004, 1.0001-1.0007, P = 0.0161) was the opposite. The differences in biological functions between the TLSGPS-based high-risk group (HRG) and low-risk group (LRG) involved cell proliferation, differentiation, and drug metabolism. HRG plus high mutations exhibited extremely poor survival. HRG had higher abundance of immune cell-oncogenic phenotypes, higher immune escape ability, and greater sensitivity to Afatinib, Dasatinib, and Gefitinib.</p><p><strong>Conclusion: </strong>3 TLSGs identified by machine learning and MR can predict the onset, prognosis and clinical treatment of HCC patients, and had significant genetic association with HCC.</p>\",\"PeriodicalId\":13859,\"journal\":{\"name\":\"International immunopharmacology\",\"volume\":\"144 \",\"pages\":\"113594\"},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2024-11-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International immunopharmacology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.intimp.2024.113594\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"IMMUNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International immunopharmacology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.intimp.2024.113594","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
Genetic association of tertiary lymphoid structure-related gene signatures with HCC based on Mendelian randomization and machine learning and construction of prognosis model.
Background: Tertiary lymphoid structures (TLS) are formed in numerous cancer types. However, their value and significance in hepatocellular carcinoma (HCC) is unclear.
Methods: We performed differential genes expression analysis of TLS-related Genes (TLSG) based on The Cancer Genome Atlas (TCGA) database, and performed Mendelian randomization (MR) analysis using expression quantitative trait loci, and then took their intersecting genes. A TLSG prognostic signature (TLSGPS)-based risk score was constructed using Least Absolute Shrinkage and Selection Operator (LASSO), univariate and multivariate COX regression analysis, and survival analysis was then performed. We used the International Cancer Genome Consortium for outside validation. We also performed biological function, tumor mutational burden, immune infiltration, single-cell analysis, CeRNA and drug sensitivity analysis based on TLSGPS.
Results: Three TLSGs (HM13, CSTB, CDCA7L) were identified to construct the TLSGPS, which showed good predictive ability and outperformed most prognostic signatures. MR suggested that HM13 (OR = 0.9997, 95 %CI: 0.9994-0.9999, P = 0.014) and CSTB (OR = 0.9997, 95 %CI: 0.9995-0.9999, P = 0.048) were negatively correlated with the risk of HCC onset, while CDCA7L (OR = 1.0004, 1.0001-1.0007, P = 0.0161) was the opposite. The differences in biological functions between the TLSGPS-based high-risk group (HRG) and low-risk group (LRG) involved cell proliferation, differentiation, and drug metabolism. HRG plus high mutations exhibited extremely poor survival. HRG had higher abundance of immune cell-oncogenic phenotypes, higher immune escape ability, and greater sensitivity to Afatinib, Dasatinib, and Gefitinib.
Conclusion: 3 TLSGs identified by machine learning and MR can predict the onset, prognosis and clinical treatment of HCC patients, and had significant genetic association with HCC.
期刊介绍：
International Immunopharmacology is the primary vehicle for the publication of original research papers pertinent to the overlapping areas of immunology, pharmacology, cytokine biology, immunotherapy, immunopathology and immunotoxicology. Review articles that encompass these subjects are also welcome.
The subject material appropriate for submission includes:
• Clinical studies employing immunotherapy of any type including the use of: bacterial and chemical agents; thymic hormones, interferon, lymphokines, etc., in transplantation and diseases such as cancer, immunodeficiency, chronic infection and allergic, inflammatory or autoimmune disorders.
• Studies on the mechanisms of action of these agents for specific parameters of immune competence as well as the overall clinical state.
• Pre-clinical animal studies and in vitro studies on mechanisms of action with immunopotentiators, immunomodulators, immunoadjuvants and other pharmacological agents active on cells participating in immune or allergic responses.
• Pharmacological compounds, microbial products and toxicological agents that affect the lymphoid system, and their mechanisms of action.
• Agents that activate genes or modify transcription and translation within the immune response.
• Substances activated, generated, or released through immunologic or related pathways that are pharmacologically active.
• Production, function and regulation of cytokines and their receptors.
• Classical pharmacological studies on the effects of chemokines and bioactive factors released during immunological reactions.
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