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Background: The aim of this study was to identify novel genetic features of Hunner's lesion interstitial cystitis (HIC) via comprehensive analysis of the Gene Expression Omnibus (GEO) database.
Methods: The GSE11783 and GSE28242 datasets were downloaded from GEO for further analysis. Differentially expressed genes (DEGs) were identified and analyzed for functional annotation. The diagnostic markers for HIC were screened and validated using the least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine recursive feature elimination (SVM-RFE) algorithms. Finally, the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm was adopted to investigate the correlation between immune cell infiltration and diagnostic markers in HIC.
Results: A total of 7837 DEGs were identified in GSE11783 and 1583 DEGs in GSE28242. Venn diagrams were used to obtain 16 overlapping upregulated and 67 overlapping downregulated DEGs separately. The LASSO logistic model and SVM-RFE algorithm were used to identify 6 genes including KRT20, SLFN11, CD86, ITGA4, PLAC8, and BTN3A3 from DEGs as diagnostic markers for HIC. Their diagnostic potential in HIC and bladder pain syndrome/interstitial cystitis (BPS/IC) were acceptable. PLAC8 exhibited the best diagnostic performance in BPS/IC with an area under the curve of 0.916. The results of immune infiltration involving GSE11783 revealed that the plasma cell ratio ( = 0.017), activated memory CD4+ T cells ( = 0.009), activated dendritic cells ( = 0.01), eosinophils ( = 0.004), and neutrophils ( = 0.03) were significantly higher in HIC than in normal samples, in contrast to resting mast cells ( = 0.022). A positive correlation existed between diagnostic markers and infiltrating immune cells.
Conclusion: KRT20, SLFN11, CD86, ITGA4, PLAC8, and BTN3A3 represent novel and potent diagnostic markers for HIC. They also exhibit certain diagnostic potential in BPS/IC. Immune cell infiltration might play a key role in the pathogenesis and progression of BPS/IC.
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http://dx.doi.org/10.2147/IJGM.S351287 | DOI Listing |
Turk J Pediatr
September 2025
Division of Allergy and Asthma, Department of Pediatrics, Faculty of Medicine, Hacettepe University, Ankara, Türkiye.
Animal allergens, particularly those from cats, dogs, and horses, are significant risk factors for the development of allergic diseases in childhood. Managing animal allergies requires allergen avoidance and, when this is not feasible, specific immunotherapy. Patient history remains the cornerstone of diagnosis, providing the foundation for diagnostic algorithms.
View Article and Find Full Text PDFAm J Reprod Immunol
September 2025
Department of Laboratory Animal Science, Kunming Medical University, Kunming, China.
Objective: To explore B cell infiltration-related genes in endometriosis (EM) and investigate their potential as diagnostic biomarkers.
Methods: Gene expression data from the GSE51981 dataset, containing 77 endometriosis and 34 control samples, were analyzed to detect differentially expressed genes (DEGs). The xCell algorithm was applied to estimate the infiltration levels of 64 immune and stromal cell types, focusing on B cells and naive B cells.
PLoS Negl Trop Dis
September 2025
Department of Clinical Science, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.
Background: Salmonella enterica encompasses over 2,600 serovars, including several commonly associated with severe infection in humans. Salmonella is a major cause of sepsis in Africa; however, diagnosis requires clinical microbiology facilities. Environmental surveillance has the potential to play a role in Salmonella surveillance.
View Article and Find Full Text PDFPLoS One
September 2025
Biobank of Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, Jiangsu, PR China.
Heart failure (HF) and lung cancer (LC) often coexist, yet their shared molecular mechanisms are unclear. We analyzed transcriptome data from the NCBI Gene Expression Omnibus (GEO) database (GSE141910, GSE57338) to identify 346 HF‑related differentially expressed genes (DEGs), then combined weighted gene co-expression network analysis (WGCNA) pinpointed 70 hub candidates. Further screening of these 70 hub candidates in TCGA lung cancer cohorts via LASSO, Random Forest, and multivariate Cox regression suggested CYP4B1 as the only independent prognostic marker.
View Article and Find Full Text PDFPLoS One
September 2025
Department of Biomedical Data Intelligence, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Capturing the dynamic changes in patients' internal states as they approach death due to fatal diseases remains a major challenge in understanding individual pathologies and improving end-of-life care. However, existing methods primarily focus on specific test values or organ dysfunction markers, failing to provide a comprehensive view of the evolving internal state preceding death. To address this, we analyzed electronic health record (EHR) data from a single institution, including 8,976 cancer patients and 77 laboratory parameters, by constructing continuous mortality prediction models based on gradient-boosting decision trees and leveraging them for temporal analyses.
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