Bioinformatics-integrated screening of systemic sclerosis-specific expressed markers to identify therapeutic targets
BackgroundSystemic sclerosis (SSc) is a rare autoimmune disease characterized by extensive skin fibrosis. There are no effective treatments due to the severity, multiorgan presentation, and variable outcomes of the disease. Here, integrated bioinformatics was employed to discover tissue-specific exp...
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Frontiers Media S.A.
2023-03-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2023.1125183/full |
| _version_ | 1797856310782328832 |
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| author | Jiahui Jin Yifan Liu Qinyu Tang Xin Yan Miao Jiang Xu Zhao Jie Chen Caixia Jin Qingjian Ou Jingjun Zhao Jingjun Zhao |
| author_facet | Jiahui Jin Yifan Liu Qinyu Tang Xin Yan Miao Jiang Xu Zhao Jie Chen Caixia Jin Qingjian Ou Jingjun Zhao Jingjun Zhao |
| author_sort | Jiahui Jin |
| collection | DOAJ |
| description | BackgroundSystemic sclerosis (SSc) is a rare autoimmune disease characterized by extensive skin fibrosis. There are no effective treatments due to the severity, multiorgan presentation, and variable outcomes of the disease. Here, integrated bioinformatics was employed to discover tissue-specific expressed hub genes associated with SSc, determine potential competing endogenous RNAs (ceRNA) regulatory networks, and identify potential targeted drugs.MethodsIn this study, four datasets of SSc were acquired. To identify the genes specific to tissues or organs, the BioGPS web database was used. For differentially expressed genes (DEGs), functional and enrichment analyses were carried out, and hub genes were screened and shown in a network of protein-protein interactions (PPI). The potential lncRNA–miRNA–mRNA ceRNA network was constructed using the online databases. The specifically expressed hub genes and ceRNA network were validated in the SSc mouse and in normal mice. We also used the receiver operating characteristic (ROC) curve to determine the diagnostic values of effective biomarkers in SSc. Finally, the Drug-Gene Interaction Database (DGIdb) identified specific medicines linked to hub genes.ResultsThe pooled datasets identified a total of 254 DEGs. The tissue/organ-specifically expressed genes involved in this analysis are commonly found in the hematologic/immune system and bone/muscle tissue. The enrichment analysis of DEGs revealed the significant terms such as regulation of actin cytoskeleton, immune-related processes, the VEGF signaling pathway, and metabolism. Cytoscape identified six gene cluster modules and 23 hub genes. And 4 hub genes were identified, including Serpine1, CCL2, IL6, and ISG15. Consistently, the expression of Serpine1, CCL2, IL6, and ISG15 was significantly higher in the SSc mouse model than in normal mice. Eventually, we found that MALAT1-miR-206-CCL2, let-7a-5p-IL6, and miR-196a-5p-SERPINE1 may be promising RNA regulatory pathways in SSc. Besides, ten potential therapeutic drugs associated with the hub gene were identified.ConclusionsThis study revealed tissue-specific expressed genes, SERPINE1, CCL2, IL6, and ISG15, as effective biomarkers and provided new insight into the mechanisms of SSc. Potential RNA regulatory pathways, including MALAT1-miR-206-CCL2, let-7a-5p-IL6, and miR-196a-5p-SERPINE1, contribute to our knowledge of SSc. Furthermore, the analysis of drug-hub gene interactions predicted TIPLASININ, CARLUMAB and BINDARIT as candidate drugs for SSc. |
| first_indexed | 2024-04-09T20:38:24Z |
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| id | doaj.art-d40ee1e3b75f4703996f30f98c50dcab |
| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-04-09T20:38:24Z |
| publishDate | 2023-03-01 |
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| series | Frontiers in Immunology |
| spelling | doaj.art-d40ee1e3b75f4703996f30f98c50dcab2023-03-30T06:57:42ZengFrontiers Media S.A.Frontiers in Immunology1664-32242023-03-011410.3389/fimmu.2023.11251831125183Bioinformatics-integrated screening of systemic sclerosis-specific expressed markers to identify therapeutic targetsJiahui Jin0Yifan Liu1Qinyu Tang2Xin Yan3Miao Jiang4Xu Zhao5Jie Chen6Caixia Jin7Qingjian Ou8Jingjun Zhao9Jingjun Zhao10Department of Dermatology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, ChinaDepartment of Dermatology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, ChinaDepartment of Dermatology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, ChinaDepartment of Dermatology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, ChinaDepartment of Dermatology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, ChinaDepartment of Dermatology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, ChinaDepartment of Dermatology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, ChinaDepartment of Dermatology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, ChinaDepartment of Dermatology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, ChinaDepartment of Dermatology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, ChinaDepartment of Dermatology, Xinhua Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, ChinaBackgroundSystemic sclerosis (SSc) is a rare autoimmune disease characterized by extensive skin fibrosis. There are no effective treatments due to the severity, multiorgan presentation, and variable outcomes of the disease. Here, integrated bioinformatics was employed to discover tissue-specific expressed hub genes associated with SSc, determine potential competing endogenous RNAs (ceRNA) regulatory networks, and identify potential targeted drugs.MethodsIn this study, four datasets of SSc were acquired. To identify the genes specific to tissues or organs, the BioGPS web database was used. For differentially expressed genes (DEGs), functional and enrichment analyses were carried out, and hub genes were screened and shown in a network of protein-protein interactions (PPI). The potential lncRNA–miRNA–mRNA ceRNA network was constructed using the online databases. The specifically expressed hub genes and ceRNA network were validated in the SSc mouse and in normal mice. We also used the receiver operating characteristic (ROC) curve to determine the diagnostic values of effective biomarkers in SSc. Finally, the Drug-Gene Interaction Database (DGIdb) identified specific medicines linked to hub genes.ResultsThe pooled datasets identified a total of 254 DEGs. The tissue/organ-specifically expressed genes involved in this analysis are commonly found in the hematologic/immune system and bone/muscle tissue. The enrichment analysis of DEGs revealed the significant terms such as regulation of actin cytoskeleton, immune-related processes, the VEGF signaling pathway, and metabolism. Cytoscape identified six gene cluster modules and 23 hub genes. And 4 hub genes were identified, including Serpine1, CCL2, IL6, and ISG15. Consistently, the expression of Serpine1, CCL2, IL6, and ISG15 was significantly higher in the SSc mouse model than in normal mice. Eventually, we found that MALAT1-miR-206-CCL2, let-7a-5p-IL6, and miR-196a-5p-SERPINE1 may be promising RNA regulatory pathways in SSc. Besides, ten potential therapeutic drugs associated with the hub gene were identified.ConclusionsThis study revealed tissue-specific expressed genes, SERPINE1, CCL2, IL6, and ISG15, as effective biomarkers and provided new insight into the mechanisms of SSc. Potential RNA regulatory pathways, including MALAT1-miR-206-CCL2, let-7a-5p-IL6, and miR-196a-5p-SERPINE1, contribute to our knowledge of SSc. Furthermore, the analysis of drug-hub gene interactions predicted TIPLASININ, CARLUMAB and BINDARIT as candidate drugs for SSc.https://www.frontiersin.org/articles/10.3389/fimmu.2023.1125183/fullsystemic sclerosistissue-specific expressed genesbiomarkersRNA regulatory pathwaydrug-gene interaction |
| spellingShingle | Jiahui Jin Yifan Liu Qinyu Tang Xin Yan Miao Jiang Xu Zhao Jie Chen Caixia Jin Qingjian Ou Jingjun Zhao Jingjun Zhao Bioinformatics-integrated screening of systemic sclerosis-specific expressed markers to identify therapeutic targets Frontiers in Immunology systemic sclerosis tissue-specific expressed genes biomarkers RNA regulatory pathway drug-gene interaction |
| title | Bioinformatics-integrated screening of systemic sclerosis-specific expressed markers to identify therapeutic targets |
| title_full | Bioinformatics-integrated screening of systemic sclerosis-specific expressed markers to identify therapeutic targets |
| title_fullStr | Bioinformatics-integrated screening of systemic sclerosis-specific expressed markers to identify therapeutic targets |
| title_full_unstemmed | Bioinformatics-integrated screening of systemic sclerosis-specific expressed markers to identify therapeutic targets |
| title_short | Bioinformatics-integrated screening of systemic sclerosis-specific expressed markers to identify therapeutic targets |
| title_sort | bioinformatics integrated screening of systemic sclerosis specific expressed markers to identify therapeutic targets |
| topic | systemic sclerosis tissue-specific expressed genes biomarkers RNA regulatory pathway drug-gene interaction |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2023.1125183/full |
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