Original Article
The Cancer Genome Atlas dataset-based analysis of aberrantly expressed genes by GeneAnalytics in thymoma associated myasthenia gravis: focusing on T cells
Abstract
Background: Myasthenia gravis (MG) is a group of autoimmune disease which could be accompanied by thymoma. Many differences have been observed between thymoma-associated MG (TAMG) and non-MG thymoma (NMG). However, the molecular difference between them remained unknown. This study aimed to explore the differentially expressed genes (DEGs) between the two categories and to elucidate the possible pathogenesis of TAMG further.
Methods: DEGs were calculated using the RNA-Sequencing data from 11 TAMG and 10 NMG in The Cancer Genome Atlas (TCGA) database. GeneAnalytics was performed to characterize the associations between DEGs and tissues and cells, diseases, gene ontology (GO) terms, pathways, phenotypes, and drug/compounds, respectively. Genes related to T cells were sorted out using LifeMapDiscovery Cells and Tissues Database. Genes directly related to the phenotype of autoimmune diseases that were identified by VarElect were validated by reverse transcription-quantitative polymerase chain reaction (RT-qPCR).
Results: The expression level of 169 genes showed a significant difference between the two groups, with 94 up-regulated and 75 down-regulated. Overexpression of six genes (ATM, SFTPB, ANKRD55, BTLA, CCR7, TNFRSF25), which are expressed in T cells and directly related to autoimmune disease through VarElect, was identified. The overexpression of soluble BTLA (sBTLA) (P=0.027), CCR7 (P=0.0018), TNFRSF25 (P=0.0013) and ANKRD55 (P=0.0026) was validated by RT-qPCR in thymoma tissues from our center.
Conclusions: Overexpression of sBTLA, CCR7, TNFRSF25 and ANKRD55 was identified and validated by RT-qPCR, which could partly explain the underlying pathogenesis in TAMG.
Methods: DEGs were calculated using the RNA-Sequencing data from 11 TAMG and 10 NMG in The Cancer Genome Atlas (TCGA) database. GeneAnalytics was performed to characterize the associations between DEGs and tissues and cells, diseases, gene ontology (GO) terms, pathways, phenotypes, and drug/compounds, respectively. Genes related to T cells were sorted out using LifeMapDiscovery Cells and Tissues Database. Genes directly related to the phenotype of autoimmune diseases that were identified by VarElect were validated by reverse transcription-quantitative polymerase chain reaction (RT-qPCR).
Results: The expression level of 169 genes showed a significant difference between the two groups, with 94 up-regulated and 75 down-regulated. Overexpression of six genes (ATM, SFTPB, ANKRD55, BTLA, CCR7, TNFRSF25), which are expressed in T cells and directly related to autoimmune disease through VarElect, was identified. The overexpression of soluble BTLA (sBTLA) (P=0.027), CCR7 (P=0.0018), TNFRSF25 (P=0.0013) and ANKRD55 (P=0.0026) was validated by RT-qPCR in thymoma tissues from our center.
Conclusions: Overexpression of sBTLA, CCR7, TNFRSF25 and ANKRD55 was identified and validated by RT-qPCR, which could partly explain the underlying pathogenesis in TAMG.
