Abstract
Resistance to anti-TNF therapy in subgroups of ulcerative colitis (UC) patients is a major challenge and incurs significant treatment costs. Identification of patients at risk of nonresponse to anti-TNF is of major clinical importance. To date, no quantitative computational framework exists to develop a complex biomarker for the prognosis of UC treatment. Modelling patient-wise receptor to transcription factor (TF) network connectivity may enable personalized treatment. We present an approach for quantitative diffusion analysis between receptors and TFs using gene expression data. Key TFs were identified using pandaR. Network connectivities between immune-specific receptor-TF pairs were quantified using network diffusion in UC patients and controls. The patient-specific network could be considered a complex biomarker that separates anti-TNF treatment-resistant and responder patients both in the gene expression dataset used for model development and separate independent test datasets. The model was further validated in rheumatoid arthritis where it successfully discriminated resistant and responder patients to tocilizumab treatment. Our model may contribute to prognostic biomarkers that may identify treatment-resistant and responder subpopulations of UC patients. Software is available at https://github.com/Amy3100/receptor2tfDiffusion. Supplementary data are available at Bioinformatics Advances online.
Highlights
This paper focuses on ulcerative colitis (UC) a subtype of inflammatory bowel disease (IBD) along with Crohn’s disease
Fifty-three IBD-relevant cytokines were selected from the 1067 identified genome-wide association studies (GWAS) risk genes for IBD (Supplementary Table S3)
A list of the selected transcription factor (TF) and receptors is available in the supplements (Supplementary Table S3), and a full list of all TFs considered with their annotations and relevant target genes (Supplementary Tables S4 and S5)
Summary
1.1 About diseaseThis paper focuses on ulcerative colitis (UC) a subtype of inflammatory bowel disease (IBD) along with Crohn’s disease. UC is a complex chronic inflammatory disease with dysregulation of the immune responses in the colonic mucosa. The disease features chronic acute relapsing disease activity, with intervals of remission (Khor et al, 2011). Microbial, environmental and genetic factors in the disease pathogenesis (Zhang and Li, 2014). Analysis of UC risk genes from genome-wide association studies (GWAS) implicates processes such as cell–cell communication, response to cytokine stimulus, and cell surface receptor intracellular signalling (Jostins et al, 2012). Targeted treatments that induce remission in subpopulations of UC patients act by inhibiting signalling pathways between extracellular signalling molecules such as cytokines, and key transcriptional regulators of inflammatory processes (Schwartz et al, 2017). We seek a method of quantifying patient-specific differences through receptor to transcription factor (TF) signalling
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