Asset Details
Do you wish to reserve the book?
Integrated Analysis of Microarray Studies to Identify Novel Diagnostic Markers in Bladder Pain Syndrome/Interstitial Cystitis with Hunner Lesion
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Integrated Analysis of Microarray Studies to Identify Novel Diagnostic Markers in Bladder Pain Syndrome/Interstitial Cystitis with Hunner Lesion
Do you wish to request the book?
Integrated Analysis of Microarray Studies to Identify Novel Diagnostic Markers in Bladder Pain Syndrome/Interstitial Cystitis with Hunner Lesion
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Integrated Analysis of Microarray Studies to Identify Novel Diagnostic Markers in Bladder Pain Syndrome/Interstitial Cystitis with Hunner Lesion
2022
Overview
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.
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.
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.
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.
Publisher
Dove Medical Press Limited,Dove Press,Dove,Dove Medical Press
