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Identification and validation of key immune-related genes with promising diagnostic and predictive value in systemic
Yajie Zhang1, Mingxin Zhu1, Limin Xie1
1National Clinical Research Center for Metabolic Diseases, Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China; Key Laboratory of Diabetes Immunology, Ministry of Education, Metabolic Syndrome Research Center, The Second Xiangya Hospital of Central South University, Changsha, China.
Aims:
To screen and confirm key immune-related genes (IRGs) with diagnostic and predictive value in systemic sclerosis (SSc) and provide potential therapeutic targets for patients with SSc.
Materials And Methods:
In Gene Expression Omnibus database (GEO), four datasets of gene expression profiling related to SSc were downloaded and used for the analysis in this study. After differential analysis of SSc cases and controls in GSE130955, the differentially expressed genes (DEGs) were overlapped with IRGs to obtain the immune-related differentially expressed genes (IR-DEGs) in SSc. In addition, functional annotation and pathway enrichment of IR-DEGs were conducted. The protein-protein interaction network (PPI) was constructed to identify key IR-DEGs. Using GSE58095, GSE181549 and GSE130953, the diagnostic and predictive abilities for the key IR-DEGs in SSc were validated. Finally, the screened key genes were confirmed in skin derived bleomycin (BLM)-induced SSc mice by Real-time PCR.
Key Findings:
NGFR, TNFSF13B, FCER1G, GIMAP5, TYROBP and CSF1R may have important or very high diagnostic value for SSc. TYROBP and TNFSF13B had moderate and mild predictive value respectively in SSc patients after treatment. Real-time PCR assay further confirmed that the expressions of Ngfr, Tyrobp, Csf1r, Fcer1g and Gimap5 were significantly higher in skin of BLM-induced SSc mice than that in controls.
Significance:
The key IR-DEGs, including NGFR, TNFSF13B, TYROBP, CSF1R, FCER1G and GIMAP5, may become auxiliary diagnostic indicators and potential biomarkers for SSc. Moreover, TNFSF13B and TYROBP could have good prospects as predictive indicators in SSc patients that accepted cyclophosphamide or transplantation therapy.
