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Imaging, Diagnosis, Prognosis |
Authors' Affiliations: Departments of 1 Pathology, 2 Genetics, 3 Radiology, and 4 Urology, Portuguese Oncology Institute–Porto, 5 Department of Pathology and Molecular Immunology, Institute of Biomedical Sciences Abel Salazar, University of Porto, and 6 School of Health Sciences, Fernando Pessoa University, Porto, Portugal; and 7 Division of Head and Neck Cancer Research, Department of Otolaryngology, Johns Hopkins University, Baltimore, Maryland
Requests for reprints: Carmen Jerónimo, Department of Genetics, Portuguese Oncology Institute–Porto, Rua Dr. António Bernardino de Almeida, 4200-072 Porto, Portugal. Phone: 351-225084000; Fax: 351-225084016; E-mail: cjeroni{at}ufp.pt.
| Abstract |
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Experimental Design: Promoter methylation levels of APC, CCND2, GSTP1, RARB2, and RASSF1A were determined by QMSP in a prospective series of 83 prostate cancer patients submitted to sextant biopsy. Clinicopathologic data [age, serum prostate-specific antigen (PSA), stage, and Gleason score] and time to progression and/or death from prostate cancer were correlated with methylation findings. Log-rank test and Cox regression model were used to identify which epigenetic markers were independent predictors of prognosis.
Results: At a median follow-up time of 45 months, 15 (18%) patients died from prostate cancer, and 37 (45%) patients had recurrent disease. In univariate analysis, stage and hypermethylation of APC were significantly associated with worse disease–specific survival, whereas stage, Gleason score, high diagnostic serum PSA levels, and hypermethylation of APC, GSTP1, and RASSF1A were significantly associated with poor disease-free survival. However, in the final multivariate analysis, only clinical stage and high methylation of APC were significantly and independently associated with unfavorable prognosis, i.e., decreased disease-free and disease-specific survival.
Conclusions: High-level APC promoter methylation is an independent predictor of poor prognosis in prostate biopsy samples and might provide relevant prognostic information for patient management.
Over the last decade, a new generation of cancer markers based on the characterization of epigenetic alterations, mainly promoter methylation, has emerged (5). We and others have reported on the value of quantitative assessment of promoter methylation of several cancer-related genes for discrimination between cancerous and noncancerous prostate tissues, allowing for the development of new early-detection strategies for PCa (reviewed in ref. 6). However, reports on the prognostic value of these epigenetic markers in tissue samples are rather scarce and are restricted to the evaluation of retrospective series of clinically localized cancers, which just represent a fraction of all prostate malignancies (7, 8).
We sought to investigate the prognostic value of promoter methylation of a panel of genes previously reported to be associated with clinicopathologic parameters of PCa progression (APC, CCND2, GSTP1, RARB2, and RASSF1A) and evaluated a model of prognosis prediction based on epigenetic alterations. For that purpose, quantitative methylation-specific PCR (QMSP) was used in a prospectively collected series of prostate biopsies from PCa suspects. Because we have previously shown that 8q gain detected in biopsies from PCa patients was associated with worse disease outcome (9), we further analyzed all genomic (molecular cytogenetic and epigenetic) data available in the same set of biopsies.
| Materials and Methods |
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Fluorogenic QMSP assays were carried out in a reaction volume of 20 µL in 384-well plates in an Applied Biosystems 7900 Sequence Detector (Perkin-Elmer). PCR was done in separate wells for each primer/probe set, and each sample was run in triplicate. The final reaction mixture consisted of 600 nmol/L of each primer (Invitrogen); 200 nmol/L probe (Applied Biosystems); 0.75 unit of platinum Taq polymerase (Invitrogen); 200 µmol/L each of dATP, dCTP, dGTP, and dTTP; 16.6 mmol/L ammonium sulfate; 67 mmol/L Trizma; 6.7 mmol/L magnesium chloride; 10 mmol/L mercaptoethanol; 0.1% DMSO, and 3 µL bisulfite-converted genomic DNA. PCR was done using the following conditions: 95°C for 2 min, followed by 50 cycles at 95°C for 15 s and 60°C for 1 min.
Each plate included multiple water blanks, a negative control, and serial dilutions of a positive control for constructing the corresponding calibration curve. Leukocyte DNA collected from healthy individuals was used as negative control. The same leukocyte DNA was methylated in vitro with SssI bacterial methyltransferase (New England Biolabs Inc.) and used as positive control for all studied genes. A given sample was considered positive when amplification was detected in at least two of the triplicates of the respective QMSP analysis. The QMSP threshold was determined for each run adjusting the best fit of the slope and R2 based on the respective calibration curve.
Statistical analysis. For statistical purposes, prostate carcinoma samples were divided into three grade categories (GS
6, GS = 7, and GS
8). Clinical stage at diagnosis comprised three categories (stage II, III, and IV). Patients were also categorized by age groups (<65 versus
65 years) and according to PSA levels (<10 ng/mL versus
10 ng/mL). Clinical variables were compared for these groups using the
2 test, Fisher's exact test, or Kruskal-Wallis nonparametric test, according to the categorization of the variables. Differences in methylation levels for the five genes studied were assessed, within the different groups of clinical variables, using the Mann-Whitney and Kruskal-Wallis nonparametric tests according to the number of categories.
The prognostic significance of available clinical variables (CS, GS, age, and PSA) was assessed by constructing disease-specific and disease-free survival curves using the Kaplan-Meier method with log-rank test (univariate test) and by a Cox-regression model comprising all four variables (multivariate test). To test the prognostic significance of the methylation status for each gene, samples were categorized into two groups based on the methylation levels for that gene [using as a threshold the value of the percentile 75; ref. 8]. Disease-specific and disease-free survival curves were then constructed based on each of the five genes (univariate analysis). A Cox-regression model comprising both clinical and epigenetic variables was computed to assess the relative contribution of each variable to the assessment of follow-up status. A P value smaller than 0.05 (two-sided) was considered to indicate statistical significance. All analyses were done using SPSS version 11.0 (SPSS).
| Results |
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In a previous study from our group, which included 55 of the cases analyzed herein, we showed that 8q gain was associated with worse disease outcome, even after stratification according to tumor grade or clinical stage (9). Thus, we analyzed the cytogenetic and epigenetic data available in this set of biopsies. Interestingly, when gain of 8q was assessed in combination with APC hypermethylation, patients with at least one of these events were more prone to relapse (P = 0.038). However, no statistically significant result was found when disease-specific survival was the end point.
| Discussion |
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These conditions might explain the significant predictive power of clinical stage but not of the GS for disease-specific survival. However, it should be stated here that the GS only attains prognostic significance after 5 years of follow-up (19), which is the upper limit of our current follow-up data. It is expected that the predictive value of the GS becomes apparent in our series in the forthcoming reevaluation of the clinical data. Therefore, the predictive value of APC hypermethylation at 60 months of follow-up is a rather significant observation, considering the clinical emphasis placed in GS for therapeutic stratification of PCa patients. Indeed, although this epigenetic alteration is correlated with GS, it also displays an independent predictive value in multivariate analysis, confirming its potential clinical usefulness. To the best of our knowledge, this is the first report of an epigenetic marker that is able to predict preoperatively the disease-specific survival of PCa patients.
Because in many studies, biochemical recurrence is a primary end point, we also tested the predictive value of methylation-based markers in this setting. Remarkably, from the five genes in the panel, only CCND2 did not show a significant association with disease-free survival in univariate analysis. However, only APC retained statistical significance in multivariate analysis. This result might be partially explained by the associations between promoter methylation levels of some genes and clinicopathologic parameters, i.e., clinical stage and GS, which were also predictors of poor survival in univariate analysis. Nevertheless, hypermethylation of APC confirmed its good performance as a prognostic factor in PCa patients for disease-free survival. Interestingly, it was previously reported that APC hypermethylation was a significant predictor for time to progression in a defined subset of PCas, i.e., GS 3 + 4 tumors (8). Our results extend this observation not only in GS range, but also in clinical stage because the tumors analyzed by Rosenbaum et al. (8) were all clinical stage II and, therefore, amenable to surgical resection. It should also be emphasized that APC hypermethylation has been reported as a promising marker for PCa detection in tissue samples (18, 20–22). Thus, determination of APC promoter methylation levels in prostate biopsies might not only constitute a valuable ancillary tool for PCa diagnosis, but it may also convey relevant prognostic information.
Because methylation levels depend on the DNA input of each sample (in this case the prostate biopsy core), we normalized the methylation results using an internal reference gene (ACTB). Owing to the marked variation in the tumor cell content of biopsy cores, it might be hypothesized that higher methylation levels could merely reflect increased tumor content, thus requiring further normalization. However, it is noteworthy that among the five target genes tested, only high APC methylation levels retained independent prognostic value. If tumor content was the major determinant of methylation levels, then the remaining genes would likely follow a similar trend. Moreover, the distribution of methylation levels according to tumor content followed different nonlinear patterns for each of the five genes, implying that biological differences are likely accounting for the observed variation among samples. Furthermore, we found that tumor content was not associated with disease-free or disease-specific survival (data not shown), and no predictive value was apparent when this parameter was included in the Cox-regression model. Thus, no subsequent adjustment to the tumor content of the biopsies was done.
A model incorporating clinical stage and APC quantitative promoter methylation provided the best strategy to stratify patients with shorter time to progression. Remarkably, it was suggested that GSTP1 promoter methylation might be a relevant prognostic serum biomarker for PCa recurrence following radical prostatectomy (7). Although the results of both studies are not directly comparable owing to the different disease spectra, our findings partially corroborate those observations, as GSTP1 quantitative promoter methylation showed prognostic significance in univariate analysis. Because Bastian et al. only tested GSTP1 methylation as a prognostic marker, no conclusions can be drawn concerning the performance of APC promoter methylation in that setting. However, because our series encompasses a wider spectrum of PCa patients, it is likely that the performance of APC hypermethylation as a serum biomarker for disease progression might also prove effective.
In previous studies from our group, we found that patients whose tumors displayed 8q gain were nine times more likely to have a poor outcome, and its prognostic significance was retained after stratification for tumor grade or clinical stage (9). The prognostic significance of 8q gain was further confirmed by fluorescence in situ hybridization in an independent series of paraffin-embedded biopsies with longer follow-up (23). When cytogenetic and epigenetic results were combined in the survival analysis, the presence of 8q gain or APC hypermethylation was associated with disease progression. The lack of statistically significant result for disease-specific survival might be explained by the lack of sufficient follow-up time, as the trend for the two groups of patients seems to indicate. Alternatively, the explanation might lie in the association of both alterations in the more aggressive set of tumors. Hence, the combined use of cytogenetic and epigenetic information might define a more powerful genomic biomarker, supporting further investigation on the integration of genomic data in disease progression assessment of PCa patients.
It should be emphasized that the results presented herein are not definitive, and further studies are planned to test our hypotheses in a larger set of prostate biopsies with longer follow-up. Importantly, both molecular cytogenetic as well as epigenetic biomarkers showed its predictive value in a pre-therapeutic setting and, thus, may provide important ancillary information for clinical decision making.
| Footnotes |
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The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/).
Under a licensing agreement between Oncomethylome Sciences, SA, and the Johns Hopkins University, Dr. Sidransky is entitled to a share of royalty received by the university on sales of products described in this article. Dr. Sidransky owns Oncomethylome Sciences, SA, stock, which is subject to certain restrictions under university policy. Dr. Sidransky is a paid consultant to Oncomethylome Sciences, SA, and is a paid member of the company's Scientific Advisory Board. The term of this arrangement is being managed by the Johns Hopkins University in accordance with its conflict of interest policies.
Received 5/ 1/07; revised 7/10/07; accepted 7/31/07.
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