ArticleTranslational andrology and urology2026
Exploration and experimental validation of oxidative stress-related diagnostic genes in interstitial cystitis based on transcriptomics.
Article in Translational andrology and urology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
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 Conclusions: Our study identifies
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