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de Maat MFG, van de Velde CJH, Benard A, Putter H, Morreau H, van Krieken JHJM, Meershoek Klein-Kranenbarg E, de Graaf EJ, Tollenaar RAEM, Hoon DSB. Identification of a quantitative MINT locus methylation profile predicting local regional recurrence of rectal cancer. Clin Cancer Res 2010; 16:2811-8. [PMID: 20460484 DOI: 10.1158/1078-0432.ccr-09-2717] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
PURPOSE Risk assessment for locoregional disease recurrence would be highly valuable in preoperative treatment planning for patients undergoing primary rectal tumor resection. Epigenetic aberrations such as DNA methylation have been shown to be significant prognostic biomarkers of disease outcome. In this study, we evaluated the significance of a quantitative epigenetic multimarker panel analysis of primary tumors to predict local recurrence in rectal cancer patients from a retrospective multicenter clinical trial. EXPERIMENTAL DESIGN Primary tumors were studied from patients enrolled in the trial who underwent total mesorectal excision for rectal cancer (n=325). Methylation levels of seven methylated-in-tumor (MINT) loci were assessed by absolute quantitative assessment of methylated alleles. Unsupervised random forest clustering of quantitative MINT methylation data was used to show subclassification into groups with matching methylation profiles. RESULTS Variable importance parameters [Gini-Index (GI)] of the clustering algorithm indicated MINT3 and MINT17 (GI, 20.2 and 20.7, respectively) to be informative for patient grouping compared with the other MINT loci (highest GI, 12.2). When using this two-biomarker panel, four different patient clusters were identified. One cluster containing 73% (184 of 251) of the patients was at significantly increased risk of local recurrence (hazard ratio, 10.23; 95% confidence interval, 1.38-75.91) in multivariate analysis, corrected for standard prognostic factors of rectal cancer. This group showed a significantly higher local recurrence probability than patients receiving preoperative radiation (P<0.0001). CONCLUSION Quantitative epigenetic subclassification of rectal cancers has clinical utility in distinguishing tumors with increased risk for local recurrence and may help tailor treatment regimens for locoregional control.
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Affiliation(s)
- Michiel F G de Maat
- Department of Molecular Oncology, John Wayne Cancer Institute, Santa Monica, California 90404, USA
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de Maat MF, van de Velde CJ, van der Werff MP, Putter H, Umetani N, Klein-Kranenbarg EM, Turner RR, van Krieken JHJ, Bilchik A, Tollenaar RA, Hoon DS. Quantitative Analysis of Methylation of Genomic Loci in Early-Stage Rectal Cancer Predicts Distant Recurrence. J Clin Oncol 2008; 26:2327-35. [DOI: 10.1200/jco.2007.14.0723] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Purpose There are no accurate prognostic biomarkers specific for rectal cancer. Epigenetic aberrations, in the form of DNA methylation, accumulate early during rectal tumor formation. In a preliminary study, we investigated absolute quantitative methylation changes associated with tumor progression of rectal tissue at multiple genomic methylated-in-tumor (MINT) loci sequences. We then explored in a different clinical patient group whether these epigenetic changes could be correlated with clinical outcome. Patients and Methods Absolute quantitative assessment of methylated alleles was used to assay methylation changes at MINT 1, 2, 3, 12, 17, 25, and 31 in sets of normal, adenomatous, and malignant tissues from 46 patients with rectal cancer. Methylation levels of these biomarkers were then assessed in operative specimens of 251 patients who underwent total mesorectal excision (TME) without neoadjuvant radiotherapy in a multicenter clinical trial. Results Methylation at MINT 2, 3, and 31 increased 11-fold (P = .005), 15-fold (P < .001), and two-fold (P = .02), respectively, during adenomatous transformation in normal rectal epithelium. Unsupervised grouping analyses of quantitative MINT methylation data of TME trial patients demonstrated two prognostic subclasses. In multivariate analysis of node-negative patients, this subclassification was the only predictor for distant recurrence (hazard ratio [HR], 4.17; 95% CI, 1.72 to 10.10; P = .002), cancer-specific survival (HR, 3.74; 95% CI, 1.4 to 9.43; P = .003), and overall survival (HR, 2.68; 95% CI, 1.41 to 5.11; P = .005). Conclusion Methylation levels of specific MINT loci can be used as prognostic variables in patients with American Joint Committee on Cancer stage I and II rectal cancer. Quantitative epigenetic classification of rectal cancer merits evaluation as a stratification factor for adjuvant treatment in early disease.
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Affiliation(s)
- Michiel F.G. de Maat
- From the Department of Molecular Oncology, John Wayne Cancer Institute; Department of Surgical Pathology, Saint John's Health Center, Santa Monica, CA; Department of Surgery, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden; and Department of Pathology, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
| | - Cornelis J.H. van de Velde
- From the Department of Molecular Oncology, John Wayne Cancer Institute; Department of Surgical Pathology, Saint John's Health Center, Santa Monica, CA; Department of Surgery, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden; and Department of Pathology, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
| | - Martijn P.J. van der Werff
- From the Department of Molecular Oncology, John Wayne Cancer Institute; Department of Surgical Pathology, Saint John's Health Center, Santa Monica, CA; Department of Surgery, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden; and Department of Pathology, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
| | - Hein Putter
- From the Department of Molecular Oncology, John Wayne Cancer Institute; Department of Surgical Pathology, Saint John's Health Center, Santa Monica, CA; Department of Surgery, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden; and Department of Pathology, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
| | - Naoyuki Umetani
- From the Department of Molecular Oncology, John Wayne Cancer Institute; Department of Surgical Pathology, Saint John's Health Center, Santa Monica, CA; Department of Surgery, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden; and Department of Pathology, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
| | - Elma Meershoek Klein-Kranenbarg
- From the Department of Molecular Oncology, John Wayne Cancer Institute; Department of Surgical Pathology, Saint John's Health Center, Santa Monica, CA; Department of Surgery, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden; and Department of Pathology, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
| | - Roderick R. Turner
- From the Department of Molecular Oncology, John Wayne Cancer Institute; Department of Surgical Pathology, Saint John's Health Center, Santa Monica, CA; Department of Surgery, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden; and Department of Pathology, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
| | - J. Han J.M. van Krieken
- From the Department of Molecular Oncology, John Wayne Cancer Institute; Department of Surgical Pathology, Saint John's Health Center, Santa Monica, CA; Department of Surgery, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden; and Department of Pathology, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
| | - Anton Bilchik
- From the Department of Molecular Oncology, John Wayne Cancer Institute; Department of Surgical Pathology, Saint John's Health Center, Santa Monica, CA; Department of Surgery, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden; and Department of Pathology, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
| | - Rob A.E.M. Tollenaar
- From the Department of Molecular Oncology, John Wayne Cancer Institute; Department of Surgical Pathology, Saint John's Health Center, Santa Monica, CA; Department of Surgery, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden; and Department of Pathology, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
| | - Dave S.B. Hoon
- From the Department of Molecular Oncology, John Wayne Cancer Institute; Department of Surgical Pathology, Saint John's Health Center, Santa Monica, CA; Department of Surgery, Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden; and Department of Pathology, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
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