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Integrated Gene Expression Profiling Analysis Reveals Probable Molecular Mechanism and Candidate Biomarker in Anti-TNFα Non-Response IBD Patients

Authors Liu Y, Duan Y, Li Y

Received 27 October 2019

Accepted for publication 14 January 2020

Published 12 February 2020 Volume 2020:13 Pages 81—95

DOI https://doi.org/10.2147/JIR.S236262

Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 3

Editor who approved publication: Dr Ning Quan


Yifan Liu, Yantao Duan, Yousheng Li

Department of General Surgery, Shanghai Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine, Shanghai 200011, People’s Republic of China

Correspondence: Yousheng Li
Department of General Surgery, Shanghai Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine, Shanghai 200011, People’s Republic of China
Email liyousheng@shemu.edu.cn

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-TNFα 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 FcγR signaling in non-response anti-TNFα 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-TNFα non-response IBD patients.
Conclusion: Over-activated interaction between FcγR-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-TNFα therapy.

Keywords: differentially expressed genes, inflammatory bowel disease, toll-like receptor pathway, FcγR signaling, anti-TNFα therapy

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