Juanjuan Hou , Yaqian Niu , Jiamin Yan , Junqiang Tian , Weitao Yu , Guoping Zhang , Tingting Li , Zhenyun Wang
{"title":"Non-invasive diagnosis for urothelial carcinoma using a dual-target DNA methylation biomarker panel","authors":"Juanjuan Hou , Yaqian Niu , Jiamin Yan , Junqiang Tian , Weitao Yu , Guoping Zhang , Tingting Li , Zhenyun Wang","doi":"10.1016/j.cca.2025.120164","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Urothelial carcinoma (UC) is a common malignancy worldwide. Aberrant DNA methylation is implicated in UC carcinogenesis. This study sought to delineate the DNA methylation landscape in UC and identify DNA methylation-based biomarkers for early detection of UC.</div></div><div><h3>Methods</h3><div>Whole genome bisulfite sequencing (WGBS) was conducted on bladder cancer tissues and paired normal tissues. By integrating WGBS data with The Cancer Genome Atlas (TCGA) UBC data, a DNA methylation-based biomarker was identified. When combined with a known UC biomarker <em>AL021918.2</em>, the performance of the dual-target test was evaluated in voided urine samples from 224 UC patients and 419 controls.</div></div><div><h3>Results</h3><div>Notable hypomethylation was observed in UC samples compared to normal samples. Through differential methylation analysis, differential methylation CpG sites, regions, and genes were identified. Of these, Transmembrane protein 106A gene (<em>TMEM106A</em>) was screened as a new UC biomarker. In a dual-target test, using triplex quantitative methylation-specific PCR (qMSP) to examine <em>TMEM106A</em> and <em>AL021918.2</em> methylation levels, the training set showed a sensitivity of 89.0 %, a specificity of 92.9 %, and an area under the curve (AUC) value of 0.941 (95 % confidence interval [CI]: 0.913–0.969). Similarly, the validation set showed a sensitivity of 90.0 %, a specificity of 91.1 %, and an AUC value of 0.922 (95 % CI: 0.881–0.962). In addition, our dual-target test demonstrated outstanding detection rates for low-grade or early-stage tumors.</div></div><div><h3>Conclusions</h3><div>We provide a comprehensive analysis of DNA methylation profiles in UC, and highlight the promising clinical potential of dual-target urine tests for UC detection.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"569 ","pages":"Article 120164"},"PeriodicalIF":3.2000,"publicationDate":"2025-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinica Chimica Acta","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0009898125000439","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICAL LABORATORY TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Urothelial carcinoma (UC) is a common malignancy worldwide. Aberrant DNA methylation is implicated in UC carcinogenesis. This study sought to delineate the DNA methylation landscape in UC and identify DNA methylation-based biomarkers for early detection of UC.
Methods
Whole genome bisulfite sequencing (WGBS) was conducted on bladder cancer tissues and paired normal tissues. By integrating WGBS data with The Cancer Genome Atlas (TCGA) UBC data, a DNA methylation-based biomarker was identified. When combined with a known UC biomarker AL021918.2, the performance of the dual-target test was evaluated in voided urine samples from 224 UC patients and 419 controls.
Results
Notable hypomethylation was observed in UC samples compared to normal samples. Through differential methylation analysis, differential methylation CpG sites, regions, and genes were identified. Of these, Transmembrane protein 106A gene (TMEM106A) was screened as a new UC biomarker. In a dual-target test, using triplex quantitative methylation-specific PCR (qMSP) to examine TMEM106A and AL021918.2 methylation levels, the training set showed a sensitivity of 89.0 %, a specificity of 92.9 %, and an area under the curve (AUC) value of 0.941 (95 % confidence interval [CI]: 0.913–0.969). Similarly, the validation set showed a sensitivity of 90.0 %, a specificity of 91.1 %, and an AUC value of 0.922 (95 % CI: 0.881–0.962). In addition, our dual-target test demonstrated outstanding detection rates for low-grade or early-stage tumors.
Conclusions
We provide a comprehensive analysis of DNA methylation profiles in UC, and highlight the promising clinical potential of dual-target urine tests for UC detection.
期刊介绍:
The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC)
Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells.
The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.