Non-invasive diagnosis for urothelial carcinoma using a dual-target DNA methylation biomarker panel

IF 2.9 3区医学 Q2 MEDICAL LABORATORY TECHNOLOGY Clinica Chimica Acta Pub Date : 2025-03-01 Epub Date: 2025-01-26 DOI:10.1016/j.cca.2025.120164

Juanjuan Hou , Yaqian Niu , Jiamin Yan , Junqiang Tian , Weitao Yu , Guoping Zhang , Tingting Li , Zhenyun Wang

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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.

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使用双靶点DNA甲基化生物标志物面板进行尿路上皮癌的非侵入性诊断。

背景：尿路上皮癌（UC）是世界范围内常见的恶性肿瘤。异常DNA甲基化与UC的癌变有关。本研究旨在描述UC中的DNA甲基化景观，并确定基于DNA甲基化的生物标志物，用于UC的早期检测。方法：对膀胱癌组织和配对正常组织进行亚硫酸氢盐全基因组测序（WGBS）。通过将WGBS数据与癌症基因组图谱（TCGA） UBC数据整合，确定了一个基于DNA甲基化的生物标志物。当与已知的UC生物标志物AL021918.2联合使用时，对224名UC患者和419名对照者的空尿样本进行了双靶点测试。结果：与正常样品相比，UC样品中观察到明显的低甲基化。通过差异甲基化分析，鉴定了差异甲基化CpG位点、区域和基因。其中，跨膜蛋白106A基因（TMEM106A）被筛选为新的UC生物标志物。在双靶点检测中，采用三重定量甲基化特异性PCR （qMSP）检测TMEM106A和AL021918.2的甲基化水平，训练集的灵敏度为89.0%，特异性为92.9%，曲线下面积（AUC）值为0.941（95%置信区间[CI]: 0.913-0.969）。同样，验证集的灵敏度为90.0%，特异性为91.1%，AUC值为0.922 （95% CI: 0.881-0.962）。因此，我们的双靶点测试在低级别或早期肿瘤中显示出出色的检出率。结论：我们提供了UC中DNA甲基化谱的全面分析，并强调了双靶点尿液检测UC的临床潜力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Clinica Chimica Acta 医学-医学实验技术

CiteScore

10.10

自引率

2.00%

发文量

1268

审稿时长

23 days

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.