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Bach S, Paulis I, Sluiter NR, Tibbesma M, Martin I, van de Wiel MA, Tuynman JB, Bahce I, Kazemier G, Steenbergen RDM. Detection of colorectal cancer in urine using DNA methylation analysis. Sci Rep 2021; 11:2363. [PMID: 33504902 PMCID: PMC7840909 DOI: 10.1038/s41598-021-81900-6] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 01/11/2021] [Indexed: 12/24/2022] Open
Abstract
Colorectal cancer (CRC) is the second leading cause for cancer-related death globally. Clinically, there is an urgent need for non-invasive CRC detection. This study assessed the feasibility of CRC detection by analysis of tumor-derived methylated DNA fragments in urine. Urine samples, including both unfractioned and supernatant urine fractions, of 92 CRC patients and 63 healthy volunteers were analyzed for DNA methylation levels of 6 CRC-associated markers (SEPT9, TMEFF2, SDC2, NDRG4, VIM and ALX4). Optimal marker panels were determined by two statistical approaches. Methylation levels of SEPT9 were significantly increased in urine supernatant of CRC patients compared to controls (p < 0.0001). Methylation analysis in unfractioned urine appeared inaccurate. Following multivariate logistic regression and classification and regression tree analysis, a marker panel consisting of SEPT9 and SDC2 was able to detect up to 70% of CRC cases in urine supernatant at 86% specificity. First evidence is provided for CRC detection in urine by SEPT9 methylation analysis, which combined with SDC2 allows for an optimal differentiation between CRC patients and controls. Urine therefore provides a promising liquid biopsy for non-invasive CRC detection.
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Affiliation(s)
- S Bach
- Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - I Paulis
- Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - N R Sluiter
- Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - M Tibbesma
- Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - I Martin
- Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1089a, Amsterdam, The Netherlands
| | - M A van de Wiel
- Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1089a, Amsterdam, The Netherlands
| | - J B Tuynman
- Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - I Bahce
- Department of Pulmonary Diseases, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - G Kazemier
- Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - R D M Steenbergen
- Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands.
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