Integrated Gene Expression Profiling Analysis Reveals Probable Molecular Mechanism and Candidate Biomarker in Anti-TNFα Non-Response IBD Patients
Integrated Gene Expression Profiling Analysis Reveals Probable Molecular Mechanism and Candidate Biomarker in Anti-TNFα Non-Response IBD Patients
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DOI：
10.2147/jir.s236262
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发表时间：
2020-01-01
影响因子：
4.5
通讯作者：
Li, Yousheng
中科院分区：
文献类型：
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作者：
Liu, Yifan;Duan, Yantao;Li, Yousheng
目的：探讨IBD患者对抗肿瘤坏死因子α制剂应答的分子机制，寻找IBD患者基因表达谱中与抗肿瘤坏死因子α制剂应答相关的候选生物标志物。方法：利用NetworkAnalyst软件整合GSE12251、GSE16879和GSE23597数据库中应答和无应答IBD患者的差异表达基因。我们对基因本体论和京都基因与基因组百科全书(KEGG)途径进行了功能浓缩分析，并从蛋白质-蛋白质相互作用网络中提取了HUB基因。通过CiberSort估计免疫细胞类型的比例。应用ROC曲线分析和二项式Lasso回归分析GSE12251、GSE16879和GSE23597以及GSE107865和GSE42296数据集中HUB基因的表达水平。它们富含14个基因本体论术语和11个KEGG途径。在无反应个体中，M2巨噬细胞到M1巨噬细胞的极化相对较高。我们发现了9个HUB基因(TLR4、TLR1、TLR8、CCR1、CD86、CCL4、HCK和FCGR2A)，它们主要与Toll样受体(TLR)通路和Fc-Gamma R信号之间的相互作用有关。FCGR2A、HCK、TLR1、TLR4、TLR8和CCL4在肠道组织中具有较高的预测价值。此外，FCGR2A、HCK和TLR8可能是抗肿瘤坏死因子α无应答IBD患者的候选血液生物标志物。结论：IBD患者天然免疫细胞中FcγR-TLR轴过度激活的相互作用可用于识别无应答个体，增加对抗肿瘤坏死因子α治疗抵抗的认识。
Purpose: To explore the molecular mechanism and search for candidate biomarkers in the gene expression profile of IBD patients associated with the response to anti-TNF alpha agents.Methods: Differentially expressed genes (DEGs) of response vs non-response IBD patients in datasets GSE12251, GSE16879, and GSE23597 were integrated using NetworkAnalyst. We conducted functional enrichment analysis of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and extracted hub genes from the protein-protein interaction network. The proportion of immune cell types was estimated via CIBERSORT. ROC curve analysis and binomial Lasso regression were applied to assess the expression level of hub genes in datasets GSE12251, GSE16879, and GSE23597, and another two datasets GSE107865 and GSE42296.Results: A total of 287 DEGs were obtained from the integrated dataset. They were enriched in 14 Gene Ontology terms and 11 KEGG pathways. Polarization from M2 to M1 macrophages was relatively high in non-response individuals. We found nine hub genes (TLR4, TLR1, TLR8, CCR1, CD86, CCL4, HCK, and FCGR2A), mainly related to the interaction between Toll-like Receptor (TLR) pathway and Fc gamma R signaling in non-response anti-TNF alpha individuals. FCGR2A, HCK, TLR1, TLR4, TLR8, and CCL4 show great value for prediction in intestinal tissue. Besides, FCGR2A, HCK, and TLR8 might be candidate blood biomarkers of anti-TNF alpha non-response IBD patients.Conclusion: Over-activated interaction between Fc gamma R-TLR axis in the innate immune cells of IBD patients might be used to identify non-response individuals and increased our understanding of resistance to anti-TNF alpha therapy.