Qian Lin, Beichen Cai, Feng Dong, Ruonan Ke, Xiuying Shan, Xuejun Ni, Lu Chen, Chuanshu Cai, Biao Wang
{"title":"综合分析发现FERMT3是瘢痕疙瘩疤痕和代谢综合征中代谢重编程的关键调节因子","authors":"Qian Lin, Beichen Cai, Feng Dong, Ruonan Ke, Xiuying Shan, Xuejun Ni, Lu Chen, Chuanshu Cai, Biao Wang","doi":"10.1007/s10142-025-01705-y","DOIUrl":null,"url":null,"abstract":"<div><p><i>Background</i>. Keloid scarring and Metabolic Syndrome (MS) are distinct conditions marked by chronic inflammation and tissue dysregulation, suggesting shared pathogenic mechanisms. Identifying common regulatory genes could unveil novel therapeutic targets. <i>Methods</i>. We performed an integrative analysis of public microarray datasets from keloid, MS, and respective healthy control tissues. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify shared gene modules. A diagnostic gene signature was developed using LASSO regression and machine learning, and validated on independent datasets. Single-cell RNA sequencing (scRNA-seq) data were analyzed to localize gene expression to specific cell types. The function of a top candidate gene, <i>FERMT3</i>, was investigated via in vitro experiments in macrophages and fibroblasts. <i>Results</i>. We identified 2,788 differentially expressed genes (DEGs) in keloids and 2,639 in MS compared to healthy controls, with 146 genes overlapping. WGCNA identified a key co-expression module (termed the “salmon” module) significantly associated with both conditions and enriched in metabolic and immune pathways. A 23-gene signature demonstrated fair to good predictive performance for both keloids (validation AUC = 0.783) and MS (AUC = 0.905). scRNA-seq analysis revealed that FERMT3 was highly expressed in macrophages and fibroblasts in keloid tissue. In vitro, modulation of FERMT3 in these cell types significantly altered their metabolic profiles (glycolysis, oxidative phosphorylation), inflammatory cytokine production, proliferation, and migration. <i>Conclusions</i>. Our integrative analysis identifies a shared transcriptomic signature between keloids and MS and highlights <i>FERMT3</i> as a key potential regulator of the metabolic and inflammatory phenotypes in these conditions. These findings suggest that <i>FERMT3</i> could be a promising therapeutic target for diseases driven by fibro-metabolic dysregulation.</p></div>","PeriodicalId":574,"journal":{"name":"Functional & Integrative Genomics","volume":"25 1","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrative analysis identifies FERMT3 as a key regulator of metabolic reprogramming in keloid scarring and metabolic syndrome\",\"authors\":\"Qian Lin, Beichen Cai, Feng Dong, Ruonan Ke, Xiuying Shan, Xuejun Ni, Lu Chen, Chuanshu Cai, Biao Wang\",\"doi\":\"10.1007/s10142-025-01705-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><i>Background</i>. Keloid scarring and Metabolic Syndrome (MS) are distinct conditions marked by chronic inflammation and tissue dysregulation, suggesting shared pathogenic mechanisms. Identifying common regulatory genes could unveil novel therapeutic targets. <i>Methods</i>. We performed an integrative analysis of public microarray datasets from keloid, MS, and respective healthy control tissues. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify shared gene modules. A diagnostic gene signature was developed using LASSO regression and machine learning, and validated on independent datasets. Single-cell RNA sequencing (scRNA-seq) data were analyzed to localize gene expression to specific cell types. The function of a top candidate gene, <i>FERMT3</i>, was investigated via in vitro experiments in macrophages and fibroblasts. <i>Results</i>. We identified 2,788 differentially expressed genes (DEGs) in keloids and 2,639 in MS compared to healthy controls, with 146 genes overlapping. WGCNA identified a key co-expression module (termed the “salmon” module) significantly associated with both conditions and enriched in metabolic and immune pathways. A 23-gene signature demonstrated fair to good predictive performance for both keloids (validation AUC = 0.783) and MS (AUC = 0.905). scRNA-seq analysis revealed that FERMT3 was highly expressed in macrophages and fibroblasts in keloid tissue. In vitro, modulation of FERMT3 in these cell types significantly altered their metabolic profiles (glycolysis, oxidative phosphorylation), inflammatory cytokine production, proliferation, and migration. <i>Conclusions</i>. Our integrative analysis identifies a shared transcriptomic signature between keloids and MS and highlights <i>FERMT3</i> as a key potential regulator of the metabolic and inflammatory phenotypes in these conditions. These findings suggest that <i>FERMT3</i> could be a promising therapeutic target for diseases driven by fibro-metabolic dysregulation.</p></div>\",\"PeriodicalId\":574,\"journal\":{\"name\":\"Functional & Integrative Genomics\",\"volume\":\"25 1\",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2025-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Functional & Integrative Genomics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10142-025-01705-y\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Functional & Integrative Genomics","FirstCategoryId":"99","ListUrlMain":"https://link.springer.com/article/10.1007/s10142-025-01705-y","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
Integrative analysis identifies FERMT3 as a key regulator of metabolic reprogramming in keloid scarring and metabolic syndrome
Background. Keloid scarring and Metabolic Syndrome (MS) are distinct conditions marked by chronic inflammation and tissue dysregulation, suggesting shared pathogenic mechanisms. Identifying common regulatory genes could unveil novel therapeutic targets. Methods. We performed an integrative analysis of public microarray datasets from keloid, MS, and respective healthy control tissues. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify shared gene modules. A diagnostic gene signature was developed using LASSO regression and machine learning, and validated on independent datasets. Single-cell RNA sequencing (scRNA-seq) data were analyzed to localize gene expression to specific cell types. The function of a top candidate gene, FERMT3, was investigated via in vitro experiments in macrophages and fibroblasts. Results. We identified 2,788 differentially expressed genes (DEGs) in keloids and 2,639 in MS compared to healthy controls, with 146 genes overlapping. WGCNA identified a key co-expression module (termed the “salmon” module) significantly associated with both conditions and enriched in metabolic and immune pathways. A 23-gene signature demonstrated fair to good predictive performance for both keloids (validation AUC = 0.783) and MS (AUC = 0.905). scRNA-seq analysis revealed that FERMT3 was highly expressed in macrophages and fibroblasts in keloid tissue. In vitro, modulation of FERMT3 in these cell types significantly altered their metabolic profiles (glycolysis, oxidative phosphorylation), inflammatory cytokine production, proliferation, and migration. Conclusions. Our integrative analysis identifies a shared transcriptomic signature between keloids and MS and highlights FERMT3 as a key potential regulator of the metabolic and inflammatory phenotypes in these conditions. These findings suggest that FERMT3 could be a promising therapeutic target for diseases driven by fibro-metabolic dysregulation.
期刊介绍:
Functional & Integrative Genomics is devoted to large-scale studies of genomes and their functions, including systems analyses of biological processes. The journal will provide the research community an integrated platform where researchers can share, review and discuss their findings on important biological questions that will ultimately enable us to answer the fundamental question: How do genomes work?