Identification and validation of tissue-based gene biomarkers for acute intestinal graft-versus-host disease(AIGVHD)
BackgroundAcute intestinal graft-versus-host disease (AIGVHD) is a common complication of allogeneic hematopoietic stem cell transplantation (allo HSCT) with a high mortality rate. The primary aim of the present study is to identify tissue-based gene biomarkers pertinent to AIGVHD, thereby facilitat...
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Frontiers Media S.A.
2025-05-01
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1574904/full |
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| author | Hong Chen Hong Chen Hong Chen Hong Chen Hong Chen Hong Chen Liyu Fu Liyu Fu Liying Liu Liying Liu Yunyan He Yunyan He Yunyan He Yunyan He Yunyan He |
| author_facet | Hong Chen Hong Chen Hong Chen Hong Chen Hong Chen Hong Chen Liyu Fu Liyu Fu Liying Liu Liying Liu Yunyan He Yunyan He Yunyan He Yunyan He Yunyan He |
| author_sort | Hong Chen |
| collection | DOAJ |
| description | BackgroundAcute intestinal graft-versus-host disease (AIGVHD) is a common complication of allogeneic hematopoietic stem cell transplantation (allo HSCT) with a high mortality rate. The primary aim of the present study is to identify tissue-based gene biomarkers pertinent to AIGVHD, thereby facilitating early diagnosis and exploration of potential therapeutic targets.MethodThe dataset was obtained from the GEO database. DEGs were identified, followed by GO and KEGG pathways analysis for the common DEGs. PPI networks and WGCNA analysis were used to identify essential genes, and correlations between critical genes and immune cell infiltration were also examined. The diagnostic efficacy of these essential genes was evaluated using ROC curves, leading to the development of 11 machine learning models based on this gene set. Furthermore, we established a mouse model of aGVHD, which was identified by clinical score, pathological analysis, flow cytometry detection of implantation rate, and immunohistochemical detection of CD4 expression. Finally, we measured the mRNA expression levels of the key genes in the mice’s intestinal tissue using real-time PCR.ResultDEGs showed a marked enrichment in immune and inflammatory response pathways. Our analysis identified three key genes, FCGR3A, SERPING1, and IFITM3, which were positively associated with M1 macrophage and neutrophil infiltration. Subsequently, we developed machine learning models utilizing these three genes and found that the RF model exhibited a robust predictive capacity for AIGVHD occurrence, achieving an AUC of 0.9802 (95% CI: 0.966–0.9945). An aGVHD mouse model was also successfully created, and we discovered that the aGVHD group’s mRNA expression levels of three key genes were noticeably higher than the control group’s.ConclusionIn this study, we identified FCGR3A, SERPING1, and IFITM3 as tissue-based gene biomarkers for AIGVHD, highlighting their diagnostic efficacy. Furthermore, we confirmed the association of these genes with AIGVHD through investigations conducted in aGVHD mouse models. |
| format | Article |
| id | doaj-art-83a5c5d54ee84faa9405cc74944af34a |
| institution | OA Journals |
| issn | 1664-3224 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Immunology |
| spelling | doaj-art-83a5c5d54ee84faa9405cc74944af34a2025-08-20T02:15:23ZengFrontiers Media S.A.Frontiers in Immunology1664-32242025-05-011610.3389/fimmu.2025.15749041574904Identification and validation of tissue-based gene biomarkers for acute intestinal graft-versus-host disease(AIGVHD)Hong Chen0Hong Chen1Hong Chen2Hong Chen3Hong Chen4Hong Chen5Liyu Fu6Liyu Fu7Liying Liu8Liying Liu9Yunyan He10Yunyan He11Yunyan He12Yunyan He13Yunyan He14Department of Pediatrics, The First Affiliated Hospital of Guangxi Medical University, Nanning, ChinaGraduate School, Guangxi Medical University, Nanning, ChinaThe Key Laboratory of Children’s Disease Research in Guangxi’s Colleges and Universities, Education Department of Guangxi Zhuang Autonomous Region, Nanning, ChinaThe first afflicted hospital of Guangxi medical university/Difficult and Criticaillness Center, Pediatric Clinical Medical Research Center of Guangxi, Nanning, ChinaNHC Key Laboratory of Thalassemia Medicine, Guangxi Medical University, Nanning, ChinaGuangxi Key Laboratory of Thalassemia Research, Guangxi Medical University, Nanning, ChinaGraduate School, Guangxi Medical University, Nanning, ChinaThe Key Laboratory of Children’s Disease Research in Guangxi’s Colleges and Universities, Education Department of Guangxi Zhuang Autonomous Region, Nanning, ChinaGraduate School, Guangxi Medical University, Nanning, ChinaThe Key Laboratory of Children’s Disease Research in Guangxi’s Colleges and Universities, Education Department of Guangxi Zhuang Autonomous Region, Nanning, ChinaDepartment of Pediatrics, The First Affiliated Hospital of Guangxi Medical University, Nanning, ChinaThe Key Laboratory of Children’s Disease Research in Guangxi’s Colleges and Universities, Education Department of Guangxi Zhuang Autonomous Region, Nanning, ChinaThe first afflicted hospital of Guangxi medical university/Difficult and Criticaillness Center, Pediatric Clinical Medical Research Center of Guangxi, Nanning, ChinaNHC Key Laboratory of Thalassemia Medicine, Guangxi Medical University, Nanning, ChinaGuangxi Key Laboratory of Thalassemia Research, Guangxi Medical University, Nanning, ChinaBackgroundAcute intestinal graft-versus-host disease (AIGVHD) is a common complication of allogeneic hematopoietic stem cell transplantation (allo HSCT) with a high mortality rate. The primary aim of the present study is to identify tissue-based gene biomarkers pertinent to AIGVHD, thereby facilitating early diagnosis and exploration of potential therapeutic targets.MethodThe dataset was obtained from the GEO database. DEGs were identified, followed by GO and KEGG pathways analysis for the common DEGs. PPI networks and WGCNA analysis were used to identify essential genes, and correlations between critical genes and immune cell infiltration were also examined. The diagnostic efficacy of these essential genes was evaluated using ROC curves, leading to the development of 11 machine learning models based on this gene set. Furthermore, we established a mouse model of aGVHD, which was identified by clinical score, pathological analysis, flow cytometry detection of implantation rate, and immunohistochemical detection of CD4 expression. Finally, we measured the mRNA expression levels of the key genes in the mice’s intestinal tissue using real-time PCR.ResultDEGs showed a marked enrichment in immune and inflammatory response pathways. Our analysis identified three key genes, FCGR3A, SERPING1, and IFITM3, which were positively associated with M1 macrophage and neutrophil infiltration. Subsequently, we developed machine learning models utilizing these three genes and found that the RF model exhibited a robust predictive capacity for AIGVHD occurrence, achieving an AUC of 0.9802 (95% CI: 0.966–0.9945). An aGVHD mouse model was also successfully created, and we discovered that the aGVHD group’s mRNA expression levels of three key genes were noticeably higher than the control group’s.ConclusionIn this study, we identified FCGR3A, SERPING1, and IFITM3 as tissue-based gene biomarkers for AIGVHD, highlighting their diagnostic efficacy. Furthermore, we confirmed the association of these genes with AIGVHD through investigations conducted in aGVHD mouse models.https://www.frontiersin.org/articles/10.3389/fimmu.2025.1574904/fullaGVHDAllo HSCTgene biomarkersimmune cell infiltrationmachine learningaGVHD mouse model |
| spellingShingle | Hong Chen Hong Chen Hong Chen Hong Chen Hong Chen Hong Chen Liyu Fu Liyu Fu Liying Liu Liying Liu Yunyan He Yunyan He Yunyan He Yunyan He Yunyan He Identification and validation of tissue-based gene biomarkers for acute intestinal graft-versus-host disease(AIGVHD) Frontiers in Immunology aGVHD Allo HSCT gene biomarkers immune cell infiltration machine learning aGVHD mouse model |
| title | Identification and validation of tissue-based gene biomarkers for acute intestinal graft-versus-host disease(AIGVHD) |
| title_full | Identification and validation of tissue-based gene biomarkers for acute intestinal graft-versus-host disease(AIGVHD) |
| title_fullStr | Identification and validation of tissue-based gene biomarkers for acute intestinal graft-versus-host disease(AIGVHD) |
| title_full_unstemmed | Identification and validation of tissue-based gene biomarkers for acute intestinal graft-versus-host disease(AIGVHD) |
| title_short | Identification and validation of tissue-based gene biomarkers for acute intestinal graft-versus-host disease(AIGVHD) |
| title_sort | identification and validation of tissue based gene biomarkers for acute intestinal graft versus host disease aigvhd |
| topic | aGVHD Allo HSCT gene biomarkers immune cell infiltration machine learning aGVHD mouse model |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1574904/full |
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