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Hypermethylation Loci of ZNF671, IRF8, and OTX1 as Potential Urine-Based Predictive Biomarkers for Bladder Cancer.
Jiang, Yuan-Hong; Liu, Yu-Shu; Wei, Yu-Chung; Jhang, Jia-Fong; Kuo, Hann-Chorng; Huang, Hsin-Hui; Chan, Michael W Y; Lin, Guan-Ling; Cheng, Wen-Chi; Lin, Shu-Chuan; Wang, Hung-Jung.
Afiliación
  • Jiang YH; Department of Urology, Hualien Tzu Chi Hospital, Tzu Chi University, Hualien 970374, Taiwan.
  • Liu YS; Guzip Biomarkers Corporation, Hsinchu City 302041, Taiwan.
  • Wei YC; Phalanx Biotech, Hsinchu City 302041, Taiwan.
  • Jhang JF; Graduate Institute of Statistics and Information Science, National Changhua University of Education, Changhua City 500207, Taiwan.
  • Kuo HC; Department of Urology, Hualien Tzu Chi Hospital, Tzu Chi University, Hualien 970374, Taiwan.
  • Huang HH; Department of Urology, Hualien Tzu Chi Hospital, Tzu Chi University, Hualien 970374, Taiwan.
  • Chan MWY; Guzip Biomarkers Corporation, Hsinchu City 302041, Taiwan.
  • Lin GL; Guzip Biomarkers Corporation, Hsinchu City 302041, Taiwan.
  • Cheng WC; Phalanx Biotech, Hsinchu City 302041, Taiwan.
  • Lin SC; Department of Biomedical Sciences, National Chung Cheng University, Minhsiung, Chiayi 621301, Taiwan.
  • Wang HJ; Epigenomics and Human Disease Research Center, National Chung Cheng University, Minhsiung, Chiayi 621301, Taiwan.
Diagnostics (Basel) ; 14(5)2024 Feb 21.
Article en En | MEDLINE | ID: mdl-38472940
ABSTRACT
Bladder cancer (BCa) is a significant health issue and poses a healthcare burden on patients, highlighting the importance of an effective detection method. Here, we developed a urine DNA methylation diagnostic panel for distinguishing between BCa and non-BCa. In the discovery stage, an analysis of the TCGA database was conducted to identify BCa-specific DNA hypermethylation markers. In the validation phase, DNA methylation levels of urine samples were measured with real-time quantitative methylation-specific PCR (qMSP). Comparative analysis of the methylation levels between BCa and non-BCa, along with the receiver operating characteristic (ROC) analyses with machine learning algorithms (logistic regression and decision tree methods) were conducted to develop practical diagnostic panels. The performance evaluation of the panel shows that the individual biomarkers of ZNF671, OTX1, and IRF8 achieved AUCs of 0.86, 0.82, and 0.81, respectively, while the combined yielded an AUC of 0.91. The diagnostic panel using the decision tree algorithm attained an accuracy, sensitivity, and specificity of 82.6%, 75.0%, and 90.9%, respectively. Our results show that the urine-based DNA methylation diagnostic panel provides a sensitive and specific method for detecting and stratifying BCa, showing promise as a standard test that could enhance the diagnosis and prognosis of BCa in clinical settings.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Diagnostics (Basel) Año: 2024 Tipo del documento: Article País de afiliación: Taiwán

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Diagnostics (Basel) Año: 2024 Tipo del documento: Article País de afiliación: Taiwán
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