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Updated: Jul 20, 2026

Perturbations of Circulating miRNAs in Irritable Bowel Syndrome Detected Using a Multiplexed High-throughput Gene Expression Platform
Published on: November 30, 2016
Exploration and experimental validation of oxidative stress-related diagnostic genes in interstitial cystitis based
Daofeng Zhang1, Junhao Zheng1, Haorui Li1
1Department of Urology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
Background:
Interstitial cystitis (IC) is a chronic pain syndrome with an elusive diagnosis and poorly understood pathogenesis, in which oxidative stress (OS) is increasingly implicated. This study aimed to identify and validate OS-related diagnostic biomarkers for IC using an integrative computational and experimental approach.
Methods:
We performed bioinformatics analysis on human bladder transcriptomic datasets (GSE11783, GSE57560) to identify OS-related differentially expressed genes (DEOSGs). Three machine learning algorithms [least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), random forest] were applied to screen for robust diagnostic markers. Immune cell infiltration was analyzed using Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT). Putative therapeutic agents were identified through the Drug Signatures Database (DSigDB) and further assessed via molecular docking and molecular dynamics (MD) simulations. The top candidate genes were validated in a cyclophosphamide-induced rat model of IC via reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) and western blotting.
Results:
We identified 58 DEOSGs in IC. Three machine learning methods consistently pinpointed S100A8 and TLR2 as key diagnostic genes. A nomogram model incorporating these genes showed high diagnostic accuracy [area under the receiver operating characteristic curve (AUC) >0.9]. Immune profiling revealed significant correlations between S100A8/TLR2 expression and specific CD4+ T cell subsets. In the IC rat model, both messenger RNA (mRNA) and protein levels of S100A8 and TLR2 were significantly upregulated. Drug repurposing analysis nominated simvastatin as a potential therapeutic agent modulating the TLR2 pathway.
Conclusions:
Our study identifies S100A8 and TLR2 as novel diagnostic biomarkers for IC. The S100A8/TLR2 axis represents a promising therapeutic target, with simvastatin highlighted as a potential repurposing candidate, offering new strategies for precise diagnosis and mechanism-based treatment of IC.
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