Yunpeng Xu, Jiajie Chen, Zhihao Huang, Rui Zhao, Can Jin, Zichen Li, Shengxiu Liu
{"title":"婴儿血管瘤坏死相关基因与免疫细胞浸润分析。","authors":"Yunpeng Xu, Jiajie Chen, Zhihao Huang, Rui Zhao, Can Jin, Zichen Li, Shengxiu Liu","doi":"10.2174/0118715303388166250901114424","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Infantile hemangioma (IH) is the most prevalent benign tumor in neonates, yet the role of necroptosis in its pathogenesis remains underexplored. This study aimed to investigate necroptosis-related gene expression patterns in IH, identify critical biomarkers, and develop a diagnostic model to enhance precision medicine approaches.</p><p><strong>Methods: </strong>Gene expression data from GSE127487 and GSE100682 datasets were analyzed to screen necroptosis-related differentially expressed genes (NRDEGs). A diagnostic model was constructed using a support vector machine (SVM) and least absolute shrinkage and selection operator (LASSO) regression. Model validity was assessed via receiver operating characteristic (ROC) curve analysis. mRNA interaction networks and immune cell associations were explored using MCPCounter algorithms and single-sample gene set enrichment analysis.</p><p><strong>Results: </strong>Seventy-four NRDEGs were identified, with six key genes highlighted. Network analysis revealed six miRNAs and 47 transcription factors associated with these genes. Additionally, six key genes showed associations with eight distinct immune cell types, suggesting potential roles in regulating the immune microenvironment.</p><p><strong>Discussion: </strong>In this study, bioinformatics was employed to analyze data, construct diagnostic models, and identify key genes.</p><p><strong>Conclusion: </strong>The six key genes may serve as reliable biomarkers for IH, offering insights into precise diagnosis and personalized therapeutic strategies. This study advances understanding of necroptosis mechanisms in IH and their interplay with immune cells.</p>","PeriodicalId":94316,"journal":{"name":"Endocrine, metabolic & immune disorders drug targets","volume":" ","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of Necroptosis-Related Genes and Immune Cell Infiltration in Infantile Hemangioma.\",\"authors\":\"Yunpeng Xu, Jiajie Chen, Zhihao Huang, Rui Zhao, Can Jin, Zichen Li, Shengxiu Liu\",\"doi\":\"10.2174/0118715303388166250901114424\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Infantile hemangioma (IH) is the most prevalent benign tumor in neonates, yet the role of necroptosis in its pathogenesis remains underexplored. This study aimed to investigate necroptosis-related gene expression patterns in IH, identify critical biomarkers, and develop a diagnostic model to enhance precision medicine approaches.</p><p><strong>Methods: </strong>Gene expression data from GSE127487 and GSE100682 datasets were analyzed to screen necroptosis-related differentially expressed genes (NRDEGs). A diagnostic model was constructed using a support vector machine (SVM) and least absolute shrinkage and selection operator (LASSO) regression. Model validity was assessed via receiver operating characteristic (ROC) curve analysis. mRNA interaction networks and immune cell associations were explored using MCPCounter algorithms and single-sample gene set enrichment analysis.</p><p><strong>Results: </strong>Seventy-four NRDEGs were identified, with six key genes highlighted. Network analysis revealed six miRNAs and 47 transcription factors associated with these genes. Additionally, six key genes showed associations with eight distinct immune cell types, suggesting potential roles in regulating the immune microenvironment.</p><p><strong>Discussion: </strong>In this study, bioinformatics was employed to analyze data, construct diagnostic models, and identify key genes.</p><p><strong>Conclusion: </strong>The six key genes may serve as reliable biomarkers for IH, offering insights into precise diagnosis and personalized therapeutic strategies. This study advances understanding of necroptosis mechanisms in IH and their interplay with immune cells.</p>\",\"PeriodicalId\":94316,\"journal\":{\"name\":\"Endocrine, metabolic & immune disorders drug targets\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2025-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Endocrine, metabolic & immune disorders drug targets\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2174/0118715303388166250901114424\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Endocrine, metabolic & immune disorders drug targets","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/0118715303388166250901114424","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of Necroptosis-Related Genes and Immune Cell Infiltration in Infantile Hemangioma.
Introduction: Infantile hemangioma (IH) is the most prevalent benign tumor in neonates, yet the role of necroptosis in its pathogenesis remains underexplored. This study aimed to investigate necroptosis-related gene expression patterns in IH, identify critical biomarkers, and develop a diagnostic model to enhance precision medicine approaches.
Methods: Gene expression data from GSE127487 and GSE100682 datasets were analyzed to screen necroptosis-related differentially expressed genes (NRDEGs). A diagnostic model was constructed using a support vector machine (SVM) and least absolute shrinkage and selection operator (LASSO) regression. Model validity was assessed via receiver operating characteristic (ROC) curve analysis. mRNA interaction networks and immune cell associations were explored using MCPCounter algorithms and single-sample gene set enrichment analysis.
Results: Seventy-four NRDEGs were identified, with six key genes highlighted. Network analysis revealed six miRNAs and 47 transcription factors associated with these genes. Additionally, six key genes showed associations with eight distinct immune cell types, suggesting potential roles in regulating the immune microenvironment.
Discussion: In this study, bioinformatics was employed to analyze data, construct diagnostic models, and identify key genes.
Conclusion: The six key genes may serve as reliable biomarkers for IH, offering insights into precise diagnosis and personalized therapeutic strategies. This study advances understanding of necroptosis mechanisms in IH and their interplay with immune cells.