Identification and validation of immune and diagnostic biomarkers for interstitial cystitis/painful bladder syndrome by integrating bioinformatics and machine-learning.

BACKGROUND

The etiology of interstitial cystitis/painful bladder syndrome (IC/BPS) remains elusive, presenting significant challenges in both diagnosis and treatment. To address these challenges, we employed a comprehensive approach aimed at identifying diagnostic biomarkers that could facilitate the assessment of immune status in individuals with IC/BPS.

METHODS

Transcriptome data from IC/BPS patients were sourced from the Gene Expression Omnibus (GEO) database. We identified differentially expressed genes (DEGs) crucial for gene set enrichment analysis. Key genes within the module were revealed using weighted gene co-expression network analysis (WGCNA). Hub genes in IC/BPS patients were identified through the application of three distinct machine-learning algorithms. Additionally, the inflammatory status and immune landscape of IC/BPS patients were evaluated using the ssGSEA algorithm. The expression and biological functions of key genes in IC/BPS were further validated through in vitro experiments.

RESULTS

A total of 87 DEGs were identified, comprising 43 up-regulated and 44 down-regulated genes. The integration of predictions from the three machine-learning algorithms highlighted three pivotal genes: PLAC8 (AUC: 0.887), S100A8 (AUC: 0.818), and PPBP (AUC: 0.871). Analysis of IC/BPS tissue samples confirmed elevated PLAC8 expression and the presence of immune cell markers in the validation cohorts. Moreover, PLAC8 overexpression was found to promote the proliferation of urothelial cells without affecting their migratory ability by inhibiting the Akt/mTOR/PI3K signaling pathway.

CONCLUSIONS

Our study identifies potential diagnostic candidate genes and reveals the complex immune landscape associated with IC/BPS. Among them, PLAC8 is a promising diagnostic biomarker that modulates the immune response in patients with IC/BPS, which provides new insights into the future diagnosis of IC/BPS.