Urine DNA methylation as a potential diagnostic and surveillance tool in non-muscle invasive bladder cancer in Thailand: A pilot study
Watcharawitayakul, T.; Ophanurak, J.; Sowanthip, D.; Somparn, P.; Pisitkun, T.; Sainamthip, P.
Show abstract
Non-muscle invasive bladder cancer (NMIBC) exhibits high recurrence, necessitating frequent invasive surveillance. Urine DNA methylation profiling represents a promising non-invasive biomarker approach for early detection and monitoring. This pilot study aimed to investigate urine DNA methylation patterns in NMIBC among Thai patients. Five patients with high-grade NMIBC and three healthy volunteers were enrolled, and midstream urine and blood samples were collected prior to transurethral resection of bladder tumor (TUR-BT). Urine cell-free DNA (cfDNA) was extracted, mechanically sheared from an atypical peak of approximately 400 bp to an optimal target length of 150-200 bp, and analyzed using cell-free methylated DNA immunoprecipitation followed by high-throughput sequencing (cfMeDIP-seq). Differentially methylated regions (DMRs) were identified between NMIBC and controls, and principal component analysis (PCA) was performed. A total of 82 DMRs were identified (adjusted P < 0.001), including 76 hypermethylated and 6 hypomethylated regions, with IRX4, TBX5, and MIR124-3 representing the top hypermethylated genes. To account for cohort heterogeneity, a refined subset analysis excluding two outlier samples (UC2 and UC3) was performed, revealing 476 significant DMRs (449 hypermethylated). PCA demonstrated clear, robust segregation between NMIBC and controls, highlighting MIR124-3, IRX4, and LHX1-DT as the most significantly hypermethylated targets. Our findings demonstrate that urine cfDNA methylation profiling can robustly distinguish NMIBC from healthy controls, highlighting MIR124-3, IRX4, and LHX1-DT as highly promising, demographic-specific biomarkers. This non-invasive approach successfully bypasses the degradative limits of traditional bisulfite conversion and establishes a technically validated foundation for clinical surveillance and diagnostics
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Bioinformatic Screen with Clinical Validation for the Identification of Novel Stool Based mRNA Biomarkers for the Detection of Colorectal Lesions Including Advanced Precancerous Lesions 92%
- Integrated RNA and metabolite profiling of urine liquid biopsies for prostate cancer biomarker discovery 91%
- Early screening of colorectal cancer using feature engineering with artificial intelligence-enhanced analysis of nanoscale chromatin modifications 91%
Similar papers in this journal
- Detection of Somatic Copy Number Deletion of CDKN2A Gene for Clinical Practices Based on Discovery of A Base-Resolution Common Deletion Region 91%
- Syngeneic model of carcinogen-induced tumor mimics basal/squamous, stromal-rich, and neuroendocrine molecular and immunological features of muscle-invasive bladder cancer 91%
- Association of the rs1042522 SNP with prostate cancer risk: a study of cancer tissues, primary tumor cultures and serum samples from a European Caucasian population 91%
Similar papers in this journal
- Development of a Single Molecule Counting Assay to Differentiate Chromophobe Renal Cancer and Oncocytoma in Clinics 91%
- Genomic and molecular associations with preoperative immune checkpoint inhibition in patients with stage III clear cell renal cell carcinoma 90%
- Loss of CHGA protein as a potential biomarker for colon cancer diagnosis: a study on biomarker discovery by machine learning and confirmation by immunohistochemistry in colorectal cancer tissue microarrays 90%
Similar papers in this journal
- Analytical performance of a highly sensitive system to detect gene variants using next-generation sequencing for lung cancer companion diagnostics 91%
- A new method for improving extraction efficiency and purity of urine and plasma cell-free DNA 89%
- Identification of prognostic biomarkers for suppressing tumorigenesis and metastasis of Hepatocellular carcinoma through transcriptome analysis 88%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.