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In-Vitro Identification and In-Vivo Confirmation of DNA Methylation Biomarkers for Urothelial Cancer
We identified DNA methylation targets specific for urothelial cancer (UC) by genome-wide methylation difference analysis of human urothelial (RT4, J82, 5637), prostate (LNCAP, DU-145, PC3) and renal (RCC-KP, CAKI-2, CAL-54) cancer cell lines with their respective primary epithelial cells. A large ov...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7459535/ https://www.ncbi.nlm.nih.gov/pubmed/32707764 http://dx.doi.org/10.3390/biomedicines8080233 |
Sumario: | We identified DNA methylation targets specific for urothelial cancer (UC) by genome-wide methylation difference analysis of human urothelial (RT4, J82, 5637), prostate (LNCAP, DU-145, PC3) and renal (RCC-KP, CAKI-2, CAL-54) cancer cell lines with their respective primary epithelial cells. A large overlap of differentially methylated targets between all organs was observed and 40 Cytosine-phosphate-Guanine motifs (CpGs) were only specific for UC cells. Of those sites, two also showed high methylation differences (≥47%) in vivo when we further compared our data to those previously obtained in our array-based analyses of urine samples in 12 UC patients and 12 controls. Using mass spectrometry, we finally assessed seven CpG sites in this “bladder-specific” region of interest in urine samples of patients with urothelial (n = 293), prostate (n = 75) and renal (n = 23) cancer, and 143 controls. DNA methylation was significantly increased in UC compared to non-UC individuals. The differences were more pronounced for males rather than females. Male UC cases could be distinguished from non-UC individuals with >30% sensitivity at 95% specificity (Area under the curve (AUC) 0.85). In summary, methylation sites highly specific in UC cell lines were also specific in urine samples of UC patients showing that in-vitro data can be successfully used to identify biomarker candidates of in-vivo relevance. |
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