Analysis and characterization of extrachromosomal circular DNA in prostate cancer: Potential biomarker discovery from urine, plasma, and tumor samples.
Extrachromosomal circular DNA (eccDNA) may contribute to genomic rearrangements and tumor heterogeneity, playing a role in cancer development and progression.
APA
Zhang M, Xu Z, et al. (2025). Analysis and characterization of extrachromosomal circular DNA in prostate cancer: Potential biomarker discovery from urine, plasma, and tumor samples.. Cancer letters, 628, 217875. https://doi.org/10.1016/j.canlet.2025.217875
MLA
Zhang M, et al.. "Analysis and characterization of extrachromosomal circular DNA in prostate cancer: Potential biomarker discovery from urine, plasma, and tumor samples.." Cancer letters, vol. 628, 2025, pp. 217875.
PMID
40516903
Abstract
Extrachromosomal circular DNA (eccDNA) may contribute to genomic rearrangements and tumor heterogeneity, playing a role in cancer development and progression. This study evaluates eccDNA as a biomarker for prostate cancer by characterizing its profiles in urine, plasma, and tumor tissues from patients at different disease stages. We studied 49 prostate cancer patients (23 early-stage; 26 late-stage, including 19 with metastasis), 23 patients with prostatitis, and 21 healthy individuals. EccDNA was extracted from plasma, urine, and tumor tissues using the Circle-Map workflow. We analyzed eccDNA abundance, genomic origin, GC content, length distribution, and repetitive sequence content. Differences among these groups were assessed with the Wilcoxon rank-sum test, and five machine learning models classified cancer vs. non-cancer based on eccDNA features. Significant variations in eccDNA levels were observed among sample types and disease states. Prostate cancer patients exhibited higher eccDNA abundance in tumor tissues compared to plasma and urine samples. Metastatic patients had significantly elevated plasma eccDNA levels compared to nonmetastatic patients and controls. Tumor-derived eccDNA showed higher GC content and distinct length distributions. Shared eccDNA molecules across tissue types suggest common origins and potential systemic roles in cancer progression. Classification models achieved strong performance, especially in plasma, where a Neural Network model reached an AUC of 0.91, and in urine, where a Random Forest model reached 0.77. Limitations include the relatively small cohort size and the need for functional studies to clarify eccDNA's role in cancer biology. This study highlights eccDNA's potential as a noninvasive biomarker for prostate cancer diagnosis and monitoring. The distinct eccDNA profiles across urine, plasma, and tumor tissues reflect disease states and progression, suggesting its utility in clinical applications.
MeSH Terms
Humans; Male; Prostatic Neoplasms; Biomarkers, Tumor; Middle Aged; Aged; DNA, Circular; Case-Control Studies
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