A urinary DNA methylation assay using two genes enables noninvasive detection and prognostic prediction in urothelial carcinoma

D Dong Wang L Lu Ai H Hongxia Tan Y Yan Yan H Hui Ye (Center of Drug Discovery, State Key Laboratory of Natural Medicines) M Meifang He C Chun-Hui Huang P Peisong Chen Y Yanping Liang R Ruizhi Wang

Abstract

Abstract The incidence of urothelial carcinoma (UC) ranks second among all urological cancers, accounting for over 90% of malignant tumors in bladder. Patients diagnosed with UC experience a lower quality of life due to rapid progression of the disease. Early and non-invasive detection is curial for diagnosing UC and improving patient outcomes. This study aimed to develop and validate a DNA methylation assay for the early detection and monitoring for UC, with a focus on its diagnostic and prognostic implications. The DNA methylation assay with real-time methylation specific polymerase chain reaction (RT-MSP) technique measures the methylation level of SOX1-OT and HIST1H4F in urine samples. A cohort comprising 436 patients diagnosed with UC or other urologic disease as well as 79 healthy patients was retrospectively utilized to evaluate this assay. Furthermore, UC patients who underwent surgery are included to assess its ability to detect recurrence. The DNA methylation assay demonstrated significantly increased methylation level in tumor tissues and a high positive rate in urine samples from UC patients. The methylation profile effectively distinguishes UC from other non-UC urologic disease, exhibiting a high sensitivity (85.2%) and specificity (90.0%) for UC diagnosis. Furthermore, the assay showed promising ability in differentiating UC patients based on tumor grade, malignancy potential, and disease stage. Additionally, the DNA methylation assay demonstrated a superior ability to detect UC recurrence with a high area under curve (AUC) of 0.979. This research proposes a novel DNA methylation assay with urine as sample for detection, representing a cost-efficient and non-invasive method for diagnosing and monitoring UC disease.

Article Details

Volume / Issue Vol. 15, Issue 1
Published August 25, 2025
ISSN 2045-2322
Publisher Nature Portfolio

Journal Info

Scientific Reports

Nature Portfolio

ISSN: 2045-2322 Open Access Life Sciences

Authors (10)

D

Dong Wang

L

Lu Ai

H

Hongxia Tan

Y

Yan Yan

H

Hui Ye

Center of Drug Discovery, State Key Laboratory of Natural Medicines

M

Meifang He

C

Chun-Hui Huang

P

Peisong Chen

Y

Yanping Liang

R

Ruizhi Wang