Diagnosis and Prognostication of Ductal Adenocarcinomas of the Pancreas Based on Genome-Wide DNA Methylation Profiling by Bacterial Artificial Chromosome Array-Based Methylated CpG Island Amplification

Gotoh, Masahiro; Arai, Eri; Wakai-Ushijima, Saori; Hiraoka, Nobuyoshi; Kosuge, Tomoo; Hosoda, Fumie; Shibata, Tatsuhiro; Kondo, Tadashi; Yokoi, Sana; Imoto, Issei; Inazawa, Johji; Kanai, Yae

doi:https://doi.org/10.1155/2011/780836

BioMed Research International

On this page

Abstract Introduction Materials and Methods Results Discussion Conclusions Supplementary Materials References Copyright Related Articles

Research Article | Open Access

Volume 2011 | Article ID 780836 | https://doi.org/10.1155/2011/780836

Diagnosis and Prognostication of Ductal Adenocarcinomas of the Pancreas Based on Genome-Wide DNA Methylation Profiling by Bacterial Artificial Chromosome Array-Based Methylated CpG Island Amplification

Masahiro Gotoh,¹Eri Arai,¹Saori Wakai-Ushijima,¹Nobuyoshi Hiraoka,¹Tomoo Kosuge,²Fumie Hosoda,³Tatsuhiro Shibata,³Tadashi Kondo,⁴Sana Yokoi,^5,6Issei Imoto,⁵Johji Inazawa,⁵and Yae Kanai¹

Academic Editor: Alain Filloux

Received22 Jul 2010

Accepted12 Nov 2010

Published21 Dec 2010

Abstract

To establish diagnostic criteria for ductal adenocarcinomas of the pancreas (PCs), bacterial artificial chromosome (BAC) array-based methylated CpG island amplification was performed using 139 tissue samples. Twelve BAC clones, for which DNA methylation status was able to discriminate cancerous tissue (T) from noncancerous pancreatic tissue in the learning cohort with a specificity of 100%, were identified. Using criteria that combined the 12 BAC clones, T-samples were diagnosed as cancers with 100% sensitivity and specificity in both the learning and validation cohorts. DNA methylation status on 11 of the BAC clones, which was able to discriminate patients showing early relapse from those with no relapse in the learning cohort with 100% specificity, was correlated with the recurrence-free and overall survival rates in the validation cohort and was an independent prognostic factor by multivariate analysis. Genome-wide DNA methylation profiling may provide optimal diagnostic markers and prognostic indicators for patients with PCs.

1. Introduction

It is known that DNA hypomethylation results in chromosomal instability as a result of changes in chromatin structure and that DNA hypermethylation of CpG islands silences tumor-related genes in cooperation with histone modification in human cancers [1–5]. The incidence of DNA methylation alterations is generally high in cancers of various organs, and particular DNA methylation profiles are significantly associated with poorer tumor differentiation, tumor aggressiveness, and poor prognosis [6–8]. Moreover, unlike alterations of mRNA and protein expression, which can be easily affected by the microenvironment of cancer cells, DNA methylation alterations are stably preserved on DNA double strands by covalent bonds and can be detected using highly sensitive methodology. Therefore, alterations of DNA methylation can become optimal diagnostic markers of cancers and prognostic indicators for affected patients.

With regard to pancreatic carcinogenesis, we have reported that accumulation of DNA methylation of tumor-related genes [9] is associated with overexpression of DNA methyltransferase (DNMT) 1 [10], the major DNMT, even in peripheral pancreatic duct epithelia with an inflammatory background, in comparison with normal peripheral pancreatic duct epithelia. Ductal adenocarcinomas of the pancreas frequently develop after chronic damage due to pancreatitis, and at least a proportion of peripheral pancreatic duct epithelia with an inflammatory background are at the precancerous stage [11]. The average number of methylated tumor-related genes and the incidence of DNMT1 overexpression increase progressively with the progression of another precancerous lesion, pancreatic intraductal neoplasia [12], to well-differentiated ductal adenocarcinoma, and finally to poorly differentiated ductal adenocarcinoma, suggesting that DNA methylation alterations participate in multistage pancreatic carcinogenesis [9, 10]. However, even though we and other groups have examined the DNA methylation status of several specific tumor-related genes [9, 13–17], only a few previous studies have employed recently developed array-based technology for analysis of DNA methylation in ductal adenocarcinomas of the pancreas [18, 19]. To our knowledge, no diagnostic criteria have yet been established for pancreatic cancers on the basis of such genome-wide DNA methylation profiling.

In the present study, in order to obtain diagnostic markers and prognostic indicators of ductal adenocarcinomas of the pancreas, we performed bacterial artificial chromosome (BAC) array-based methylated CpG island amplification (BAMCA) [20–22], which is a technique suitable for overviewing the DNA methylation tendency of individual large regions among all chromosomes [23, 24], in samples of normal pancreatic tissue obtained from patients without ductal adenocarcinomas (C), noncancerous pancreatic tissue obtained from patients with ductal adenocarcinomas (N), and cancerous tissue (T).

2. Materials and Methods

2.1. Patients and Tissue Samples

Ninety-one T-samples were obtained from surgically resected specimens from patients with ductal adenocarcinomas who underwent pancreatectomy at the National Cancer Center Hospital, Tokyo, Japan, between 2003 and 2008. From 33 of the 91 patients, N-samples were also obtained from the same surgically resected specimens. Microscopic examination of the histological specimens taken from a region immediately adjoining that from which N-samples had been obtained revealed various degrees of chronic pancreatitis, but no contaminating cancer cells. Fifteen C-samples were obtained from patients without ductal adenocarcinomas who underwent pancreatectomy for metastasis of renal cell carcinoma (1 patient), adenocarcinoma of the gallbladder (3 patients), adenocarcinoma of the papilla of Vater (6 patients), serous cystadenoma (1 patient), mucinous cystadenoma (1 patient), solid-pseudopapillary neoplasm (1 patient), endocrine tumor (1 patient) of the pancreas, and lymphoplasmacytic pancreatitis (1 patient). The total samples were randomly divided into a learning cohort (8 C-, 17 N-, and 46 T-samples) and a validation cohort (7 C-, 16 N-, and 45 T-samples). In the learning cohort, patients from whom C-, N-, and T-samples were obtained comprised 5 men and 3 women with a mean age of (mean ± SD) years, 6 men and 11 women with a mean age of years, and 28 men and 18 women with a mean age of years, respectively. In the validation cohort, the patients from whom C-, N-, and T-samples were obtained comprised 3 men and 4 women with a mean age of years, 11 men and 5 women with a mean age of years, and 27 men and 18 women with a mean age of years, respectively. The clinicopathological parameters of patients who provided T-samples in both the learning and validation cohorts are summarized in Table 1. This study was approved by the Ethics Committee of the National Cancer Center, Tokyo, Japan, and was performed in accordance with the Declaration of Helsinki, 1995. All patients gave their informed consent prior to their inclusion in this study.

2.2. BAMCA

High-molecular-weight DNA from fresh frozen tissue samples was extracted using phenol-chloroform, followed by dialysis. DNA methylation status was analyzed by BAMCA using a custom-made array (MCG Whole Genome Array-4500) harboring 4361 BAC clones located throughout chromosomes 1 to 22, X and Y [25], as described previously [23, 26, 27]. Briefly, a mixture of normal pancreatic tissue DNA obtained from 8 C-samples in the learning cohort was used as a reference for all analyses of test DNA samples in both the learning and validation cohorts. Five-microgram aliquots of test or reference DNA were first digested with 100 units of methylation-sensitive restriction enzyme Sma I (NEB, Ipswich, MA) and subsequently with 20 units of methylation-insensitive Xma I (NEB). Adapters were ligated to Xma I-digested sticky ends, and polymerase chain reaction (PCR) was performed with an adapter primer set. Test and reference PCR products were labeled by random priming with Cy3- and Cy5-dCTP (GE Healthcare, Buckinghamshire, UK), respectively, and precipitated together with ethanol in the presence of Cot-I DNA (Invitrogen, Carlsbad, CA). The mixture was applied to array slides and incubated at 43°C for 63 h. Arrays were scanned with a GenePix Personal 4100A (Molecular Devices, Sunnyvale, CA) and analyzed using GenePix Pro 5.0 imaging software (Molecular Devices) and Acue 2 software (Mitsui Knowledge Industry, Tokyo, Japan). The signal ratios were normalized in each sample to make the mean signal ratios of all BAC clones 1.0. The reproducibility of BAMCA data was confirmed in representative samples by the duplicate study (data not shown).

2.3. Statistics

BAC clones whose signal ratios obtained by BAMCA differed significantly between the groups of samples were identified by Wilcoxon test. Survival curves of patient groups were calculated by the Kaplan-Meier method, and the differences were compared using the Log-rank test. The Cox proportional hazards multivariate model was used to examine the prognostic impact of DNA methylation status, surgical margin status (R0 versus R1 or R2) [28] and lymph node metastasis. Differences at were considered significant.

3. Results

3.1. Genome-Wide DNA Methylation Alterations in Tissue Samples

Figure 1 shows representative examples of scanned array images and scattergrams of the signal ratios (test signal/ reference signal) for a C-sample, a N-sample, and the corresponding T-sample. In all C-samples, the signal ratios of 97% of the BAC clones were between 0.67 and 1.5 (red lines in Figure 1(b)). Therefore, in N- and T-samples, DNA methylation status corresponding to a signal ratio of less than 0.67 and more than 1.5 was defined as DNA hypo- and hypermethylation of each BAC clone relative to C-samples, respectively, as in our previous studies [23, 26, 27]. In N-samples, many BAC clones showed DNA hypo- or hypermethylation (Figure 1(b)). In T-samples, more BAC clones showed DNA hypo- or hypermethylation, and the degree of DNA hypo- or hypermethylation, that is, deviation of the signal ratio from 0.67 or 1.5, was increased in comparison with N-samples (Figure 1(b)).

(a)

(b)

Figure 1

Genome-wide DNA methylation analysis by BAMCA. (a) Representative examples of scanned array images in a sample of normal pancreatic tissue obtained from a patient without ductal adenocarcinoma of the pancreas (C) and samples of both noncancerous pancreatic tissue (N) and cancerous tissue (T) obtained from a single patient with ductal adenocarcinoma of the pancreas. Test and reference DNA labeled with Cy3 and Cy5 was cohybridized, respectively. (b) Representative examples of scattergrams of the signal ratios (test signal/ reference signal) in each C-, N-, and T-sample. In all C-samples, the signal ratios of 97% of the BAC clones were between 0.67 and 1.5 (red lines). Therefore, in N- and T samples, DNA methylation status corresponding to a signal ratio of less than 0.67 and more than 1.5 was defined as DNA hypo- and hypermethylation on each BAC clone relative to C-samples, respectively. In N-samples, many BAC clones showed DNA hypo- or hypermethylation. In T-samples, more BAC clones showed DNA hypo- or hypermethylation, and the degree of DNA hypo- or hypermethylation, that is, deviation of the signal ratio from 0.67 or 1.5, was increased in comparison with N-samples.

3.2. Establishment of Criteria for Diagnosis of Ductal Adenocarcinomas of the Pancreas Based on DNA Methylation Profiles

Wilcoxon test () revealed that the average signal ratios of 331 BAC clones (Supplementary Table SI available at http://dx.doi.org/10.1155/2011/780836) in T-samples differed significantly from those in both C- and N-samples. Figure 2(a) shows scattergrams of the signal ratios for representative examples of the 331 BAC clones: RP11-88P10 and RP11-424K7 were able to discriminate T-samples from both C- and N-samples with 100% specificity (the ratio of the number of true negatives to the number of true negatives and false positives) using cutoff values of 0.86 and 1.29 (dotted lines in Figure 2(a)), respectively, (specificity was calculated as the ratio of the number of C- and N-samples showing signal ratios of 0.86 or more than 0.86 and 1.29 or less than 1.29 relative to the total number of C- and N-samples, resp.). The cutoff values of the signal ratios and sensitivities (the ratios of the number of true positives to the number of true positives and false negatives) of 12 BAC clones for which such discrimination was performed with 100% specificity are shown in Table 2. Genes located on the 12 BAC clones are summarized in Supplementary Table SII. A histogram showing the number of BAC clones satisfying the criteria listed in Table 2 in 8 C-samples, 17 N-samples, and 46 T-samples in the learning cohort is shown in Figure 2(b). Based on this histogram, we finally established the following criteria: when tissue samples satisfied the criteria in Table 2 for 1 or more BAC clones, they were judged to be ductal adenocarcinomas, and when tissue samples did not satisfy the criteria for any BAC clone, they were judged not to be ductal adenocarcinomas. Based on these criteria, both the sensitivity and specificity for diagnosis of T-samples in the learning cohort as ductal adenocarcinomas were 100% (sensitivity was calculated as the ratio of the number of T-samples satisfying the criteria in Table 2 for 1 or more BAC clones to the total number of T-samples, and specificity was calculated as the ratio of the number of C- and N-samples not satisfying the criteria in Table 2 for any BAC clone relative to the total number of C- and N-samples).

(a)

(b)

(c)

Figure 2

Establishment of criteria for diagnosis of ductal adenocarcinomas of the pancreas. (a) Scattergrams of the signal ratios in samples of normal pancreatic tissue obtained from patients without ductal adenocarcinomas (C), noncancerous pancreatic tissue obtained from patients with ductal adenocarcinomas (N) and cancerous tissue (T) on representative BAC clones, RP11-88P10 and RP11-424K7. Using the cutoff values indicated by the dotted lines, T-samples were discriminated from both C- and N-samples in the learning cohort with 100% specificity. (b) Histogram showing the number of BAC clones satisfying the criteria listed in Table 2 in the learning cohort (). C-, N- and T-samples are indicated by empty, shaded, and filled columns, respectively. Based on this histogram, we established the following criteria: when the tissue samples satisfied the criteria listed in Table 2 for 1 or more BAC clones (dotted line), they were judged to be cancerous tissue, and when tissue samples did not satisfy the criteria for any BAC clone, they were judged not to be cancerous tissue. Based on these criteria, both the sensitivity and specificity for diagnosis of T-samples in the learning cohort as being cancerous were 100%. (c) Validation of the above criteria using 68 additional tissue samples in the validation cohort. All 45 validation samples satisfying the criteria in Table 2 for 1 or more BAC clones (dotted line) were T-samples (filled columns), and all 23 validation samples not satisfying the criteria in Table 2 for any BAC clone were C- (empty column) or N- (shaded column) samples. Both the sensitivity and specificity for diagnosis of T-samples in the validation cohort as being cancerous were again 100%.

To confirm these criteria, 68 additional tissue samples in the validation cohort were analyzed. Forty-five samples satisfying the criteria listed in Table 2 for 1 or more BAC clones were all T-samples, and the other 23 samples not satisfying the criteria listed in Table 2 for any BAC clone were all C- or N-samples (Figure 2(c)). Our criteria enabled diagnosis of T-samples in the validation cohort as ductal adenocarcinomas with 100% sensitivity and specificity.

3.3. Establishment of Criteria for Prognostication of Patients with Ductal Adenocarcinomas of the Pancreas Based on DNA Methylation Profiles

To establish criteria for prognostication, 21 patients who had not undergone adjuvant chemotherapy with gemcitabine in the learning cohort were divided into two groups: 4 patients who had not suffered relapse for more than 4 years after pancreatectomy and 17 patients who had suffered relapse within 18 months after pancreatectomy were defined as the no-relapse group and early-relapse group, respectively. The period covered ranged from 215 to 1,846 days (mean, 823 days). Wilcoxon test () revealed that the average signal ratios of 64 BAC clones differed significantly between T-samples obtained from the no-relapse group and those from the early-relapse group.

Figure 3(a) shows scattergrams of the signal ratios for representative examples of the 64 BAC clones: RP11-165B11 and RP11-92A14 were able to discriminate T-samples from patients belonging to the early-relapse group from those belonging to the no-relapse group with 100% specificity (the ratio of the number of true negatives to the number of true negatives and false positives) using cutoff values of 1.29 and 1.03 (dotted lines in Figure 3(a)), respectively, (specificity was calculated as the ratio of the number of T-samples from patients belonging to the no-relapse group showing signal ratios of 1.29 or more than 1.29 and 1.03 or less than 1.03 relative to the total number of T-samples from patients belonging to the no-relapse group, resp.). The cutoff values of the signal ratios and sensitivities (the ratios of the number of true positives to the number of true positives and false negatives) of 11 BAC clones for which such discrimination was performed with 100% specificity are shown in Table 3. Genes located on the 11 BAC clones are summarized in Supplementary Table SII. A histogram showing the number of BAC clones satisfying the criteria listed in Table 3 in 4 T-samples from the no-relapse group and 17 T-samples from the early-relapse group in the learning cohort is shown in Figure 3(b). Based on these criteria (2 or more BAC clones versus less than 2 BAC clones listed in Table 3), both the sensitivity and specificity of discrimination of patients belonging to the early-relapse group from those belonging to the no-relapse group in the learning cohort were 100% (sensitivity was calculated as the ratio of the number of T-samples from patients belonging to the early-relapse group satisfying the criteria in Table 3 for 2 or more BAC clones relative to the total number of T-samples from patients belonging to the early-relapse group, and specificity was calculated as the ratio of the number of T-samples from patients belonging to the no-relapse group satisfying the criteria in Table 3 for less than 2 BAC clones relative to the total number of T-samples from patients belonging to the no-relapse group).

(a)

(b)

(c)

Figure 3

Establishment of criteria for prognostication of patients with ductal adenocarcinomas of the pancreas. (a) Scattergrams of the signal ratios in samples of cancerous tissue obtained from patients in the no-relapse group (NR, ) and early-relapse group (ER, ) who had not undergone adjuvant chemotherapy with gemcitabine after surgery on representative bacterial artificial chromosome (BAC) clones, RP11-165B11 and RP11-92A14. Using the cutoff values indicated by the dotted lines, patients belonging to the ER-group were discriminated from those belonging to the NR-group in the learning cohort with 100% specificity. (b) Histogram showing the number of BAC clones satisfying the criteria listed in Table 3 for patients belonging to the NR- (shaded column) and ER- (filled columns) groups in the learning cohort. (c) Kaplan-Meier survival curves of 34 patients who had not undergone adjuvant chemotherapy with gemcitabine after surgery in the validation cohort. Both the recurrence-free and overall survival rates of 29 patients satisfying the criteria listed in Table 3 for 2 or more BAC clones (solid lines) were significantly lower than those of 5 patients satisfying the criteria listed in Table 3 for less than 2 BAC clones (dotted lines). Log-rank test ( and , resp.).

To confirm these criteria, 34 additional T-samples obtained from patients who had not undergone adjuvant chemotherapy with gemcitabine after surgery in the validation cohort were analyzed. The period covered ranged from 92 to 2,274 days (mean, 612 days). Both the recurrence-free and overall survival rates of 29 patients satisfying the criteria listed in Table 3 for 2 or more BAC clones were significantly lower than those of 5 patients satisfying the criteria listed in Table 3 for less than 2 BAC clones (Figure 3(c), and , resp.).

Moreover, multivariate analysis in all 91 patients with ductal adenocarcinomas revealed that satisfying the criteria listed in Table 3 for 2 or more BAC clones was a prognostic parameter for both recurrence-free and overall survival that was independent of surgical margin positivity (R1 or R2) [28] and lymph node metastasis at the time of surgery, which are known to have a prognostic impact [29–33] (Table 4).

4. Discussion

Ductal adenocarcinoma of the pancreas, one of the most lethal of all human cancers, is now a common cause of cancer mortality in the United States and Japan [34]. Due to its aggressive growth behavior with early local spread into the surrounding tissues mostly along neural sheaths, peritoneal dissemination, and liver and lymph node metastasis, the prognosis remains poor. Surgical treatment still provides the only possibility of cure [35]. Although advances in preoperative diagnostic imaging have made it possible to detect tumors at an early stage when they are still resectable, diagnosis using pancreatic biopsy and/or specimens of pancreatic juice is indispensable before surgery. In general, pancreatic biopsy yields only a small amount of tissue, and in pancreatic juice specimens, the cellular morphology is not well preserved due to degeneration. Therefore, molecular diagnosis is advantageous for supporting the histological and/or cytological assessment of such specimens. DNA methylation profiles, which are stably preserved on DNA double strands by covalent bonds, even after degeneration of cellular morphology, may become diagnostic markers in pancreatic biopsy and/or pancreatic juice specimens.

We have previously established diagnostic criteria for cancers of the kidney [26], liver [27] and urinary tract [23] based on genome-wide DNA methylation profiles using the BAC array-based approach, BAMCA, which can assess DNA methylation status not only on promoter regions of specific tumor-related genes but also on genomic regions in which DNA hypomethylation affects chromosomal instability. Moreover, during human carcinogenesis, DNA methylation status is frequently altered in a coordinated manner, through processes such as long-range epigenetic silencing [36], in large chromosome regions. Since BAMCA is suitable for overviewing the DNA methylation tendency of individual large regions among all chromosomes [23, 24], we again employed this method to establish diagnostic criteria for ductal adenocarcinomas of the pancreas.

The results of BAMCA for C-samples reflected the DNA methylation profiles of normal peripheral pancreatic duct epithelia (the origin of ductal adenocarcinomas), acinar cells and islet cells. In N-samples, BAMCA revealed DNA hypo- or hypermethylation on many BAC clones in comparison to C-samples (Figure 1(b)). Microscopic observation of N-samples revealed lymphocytes and fibroblasts associated with various degrees of chronic pancreatitis, which is considered to be one of the precancerous conditions for ductal adencarcinomas [11]. Our previous studies using microdissection and immunohistochemistry revealed accumulation of DNA hypermethylation of tumor-related genes associated with DNMT1 overexpression, even in peripheral pancreatic duct epithelia at the precancerous stage [9, 10]. Therefore, the results of BAMCA for N-samples may reflect the DNA methylation profiles of peripheral pancreatic duct epithelia at the precancerous stage, lymphocytes, fibroblasts, acinar cells, and islet cells. In order to diagnose ductal adenocarcinomas in tissue samples, cancer-specific DNA methylation profiles should be discriminated from those of normal or precancerous peripheral pancreatic duct epithelia, lymphocytes, fibroblasts, acinar cells, and islet cells. Therefore, we identified 12 BAC clones whose DNA methylation status was able to discriminate T-samples from both C- and N-samples.

In both the learning and validation cohorts, the criteria combining the 12 BAC clones were able to diagnose T-samples as ductal adenocarcinomas with a sensitivity and specificity of 100%. Our criteria may be advantageous for supporting the histological diagnosis of tiny tissue samples obtained by pancreatic biopsy. Discrimination of cancer cells from exfoliated noncancerous epithelial cells and lymphocytes using the 12 BAC clones may be applicable for diagnosis using specimens of pancreatic juice. Development of methodology for assessing DNA methylation status on the 12 BAC clones in fewer cells may be more advantageous for clinical application, as we have already established a methodology for quantification of DNA methylation levels on specific CpG sites in a very small quantity of genomic DNA for estimation of carcinogenetic risk in patients with chronic liver diseases (unpublished data). Development of this methodology means that if DNA methylation alterations on the 12 BAC clones are not observed in circulating blood cells, our criteria may become applicable for noninvasive diagnosis of pancreatic cancers based on serum markers that differ from the widely used carbohydrate antigen 19-9, whose serum levels are also elevated in patients with chronic pancreatitis [37].

Even when resection with curative intent is performed for patients with pancreatic cancers, the rate of disease recurrence is high and the survival rate after surgery is poor. As surgical resection alone has limitations, development of nonsurgical treatments, including adjuvant therapy, is needed in order to improve the prognosis of patients with pancreatic cancers. Although previous studies have suggested the efficacy of adjuvant chemotherapy [38], it should be carried out carefully, paying close attention to adverse reactions [39]. In order to help decide the indications for such adjuvant chemotherapy after surgery, prognostic indicators should be explored. The criteria listed in Table 3 were able to discriminate the early-relapse group from the no-relapse group with 100% sensitivity and specificity in the learning cohort. Significant correlation between DNA methylation status on the 11 BAC clones and the recurrence-free and overall survival rates of patients with ductal adenocarcinomas in the validation cohort validated the criteria. Multivariate analysis revealed that our criteria were able to predict recurrence-free and overall patient outcome independently of parameters that had been reported to be significantly prognostic in many previous studies, such as surgical margin positivity (R1 or R2) [28] and lymph node metastasis. Therefore, prognostication based on our criteria may be promising for supportive use during followup after surgical resection in patients with ductal adenocarcinomas of the pancreas. Since histological heterogeneity is frequently observed even in a ductal adenocarcinoma of the pancreas from a single patient, the consistency of BAMCA data for multiple T-samples obtained from a single tumor should be carefully confirmed in a prospective validation study before clinical application of the prognostic criteria.

5. Conclusions

BAMCA revealed genome-wide DNA methylation alterations in ductal adenocarcinomas of the pancreas. Criteria combining the DNA methylation status on 12 BAC clones were able to discriminate T-samples from both C- and N-samples and to diagnose T-samples as ductal adenocarcinomas, with 100% sensitivity and specificity in both the learning and validation cohorts. Satisfying the criteria using 11 BAC clones was able to predict the recurrence-free and overall survival of patients with ductal adenocarcinomas independently of surgical margin positivity (R1 or R2) [28] and lymph node metastasis. Genome-wide DNA methylation profiling may provide optimal diagnostic markers for pancreatic cancers and prognostic indicators for affected patients.

Abbreviation

BAC:	Bacterial artificial chromosome
BAMCA:	BAC array-based methylated CpG island amplification
DNMT:	DNA methyltransferase.

Acknowledgment

This study was supported by a Grant-in-Aid for the Third Term Comprehensive 10-Year Strategy for Cancer Control from the Ministry of Health, Labor and Welfare of Japan, a Grant-in-Aid for Cancer Research from the Ministry of Health, Labor and Welfare of Japan, a Grant from the New Energy and Industrial Technology Development Organization (NEDO), and the Program for Promotion of Fundamental Studies in Health Sciences of the National Institute of Biomedical Innovation (NiBio).

Conflict of Interests

There is no potential conflict of interests to disclose.

Supplementary Materials

Wilcoxon test (P < .01) revealed that the average signal ratios of the 331 BAC clones in samples of cancerous tissue (T) differed significantly from those in both samples of normal pancreatic tissue obtained from patients without ductal adenocarcinomas (C) and samples of noncancerous pancreatic tissue obtained from patients with ductal adenocarcinomas (N) in the learning cohort. Such 331 BAC clones are listed and their chromosomal loci based on the UCSC Genome Browser (http://genome.ucsc.edu/cgi-bin/hgGateway) are summarized in Supplementary Table SI.

In 12 BAC clones, using cutoff values of the signal ratios shown in Table 2, samples of cancerous tissue were discriminated from both samples of normal pancreatic tissue obtained from patients without ductal adenocarcinomas and samples of noncancerous pancreatic tissue obtained from patients with ductal adenocarcinomas in the learning cohort with 100% specificity. Genes located on the 12 BAC clones are summarized in Supplementary Table SII (a). In 11 BAC clones, using cutoff values of the signal ratios shown in Table 3, samples of cancerous tissue from patients belonging to the early-relapse group were discriminated from those belonging to the no-relapse group in the learning cohort with 100% specificity. Genes located on the 11 BAC clones are summarized in Supplementary Table SII (b).

Supplementary Material

References

P. A. Jones and S. B. Baylin, “The fundamental role of epigenetic events in cancer,” Nature Reviews Genetics, vol. 3, no. 6, pp. 415–428, 2002.
View at: Google Scholar
S. B. Baylin and J. E. Ohm, “Epigenetic gene silencing in cancer—a mechanism for early oncogenic pathway addiction?” Nature Reviews Cancer, vol. 6, no. 2, pp. 107–116, 2006.
View at: Publisher Site | Google Scholar
P. A. Jones and S. B. Baylin, “The epigenomics of cancer,” Cell, vol. 128, no. 4, pp. 683–692, 2007.
View at: Publisher Site | Google Scholar
M. Ehrlich, “DNA hypomethylation in cancer cells,” Epigenomics, vol. 1, no. 2, pp. 239–259, 2009.
View at: Google Scholar
S. Sharma, T. K. Kelly, and P. A. Jones, “Epigenetics in cancer,” Carcinogenesis, vol. 31, no. 1, pp. 27–36, 2010.
View at: Publisher Site | Google Scholar
Y. Kanai and S. Hirohashi, “Alterations of DNA methylation associated with abnormalities of DNA methyltransferases in human cancers during transition from a precancerous to a malignant state,” Carcinogenesis, vol. 28, no. 12, pp. 2434–2442, 2007.
View at: Publisher Site | Google Scholar
Y. Kanai, “Alterations of DNA methylation and clinicopathological diversity of human cancers,” Pathology International, vol. 58, no. 9, pp. 544–558, 2008.
View at: Publisher Site | Google Scholar
Y. Kanai, “Genome-wide DNA methylation profiles in precancerous conditions and cancers,” Cancer Science, vol. 101, no. 1, pp. 36–45, 2010.
View at: Publisher Site | Google Scholar
D. F. Peng, Y. Kanai, M. Sawada et al., “DNA methylation of multiple tumor-related genes in association with overexpression of DNA methyltransferase 1 (DNMT1) during multistage carcinogenesis of the pancreas,” Carcinogenesis, vol. 27, no. 6, pp. 1160–1168, 2006.
View at: Publisher Site | Google Scholar
D. F. Peng, Y. Kanai, M. Sawada et al., “Increased DNA methyltransferase 1 (DNMT1) protein expression in precancerous conditions and ductal carcinomas of the pancreas,” Cancer Science, vol. 96, no. 7, pp. 403–408, 2005.
View at: Publisher Site | Google Scholar
N. Howes and J. P. Neoptolemos, “Risk of pancreatic ductal adenocarcinoma in chronic pancreatitis,” Gut, vol. 51, no. 6, pp. 765–766, 2002.
View at: Publisher Site | Google Scholar
R. H. Hruban, N. V. Adsay, J. Albores-Saavedra et al., “Pancreatic intraepithelial neoplasia: a new nomenclature and classification system for pancreatic duct lesions,” American Journal of Surgical Pathology, vol. 25, no. 5, pp. 579–586, 2001.
View at: Publisher Site | Google Scholar
J. Attri, R. Srinivasan, S. Majumdar, B. D. Radotra, and J. Wig, “Alterations of tumor suppressor gene p16 in pancreatic ductal carcinoma,” BMC Gastroenterology, vol. 5, article 22, 2005.
View at: Publisher Site | Google Scholar
S. Xu, T. Furukawa, N. Kanai, M. Sunamura, and A. Horii, “Abrogation of DUSP6 by hypermethylation in human pancreatic cancer,” Journal of Human Genetics, vol. 50, no. 4, pp. 159–167, 2005.
View at: Publisher Site | Google Scholar
N. Sato, H. Matsubayashi, N. Fukushima, and M. Goggins, “The chemokine receptor CXCR4 is regulated by DNA methylation in pancreatic cancer,” Cancer Biology and Therapy, vol. 4, no. 1, pp. 70–76, 2005.
View at: Google Scholar
S. Nomoto, T. Kinoshita, T. Mori et al., “Adverse prognosis of epigenetic inactivation in RUNX3 gene at 1p36 in human pancreatic cancer,” British Journal of Cancer, vol. 98, no. 10, pp. 1690–1695, 2008.
View at: Publisher Site | Google Scholar
X. M. Bu, C. H. Zhao, N. Zhang, F. Gao, S. Lin, and X. W. Dai, “Hypermethylation and aberrant expression of secreted fizzled-related protein genes in pancreatic cancer,” World Journal of Gastroenterology, vol. 14, no. 21, pp. 3421–3424, 2008.
View at: Publisher Site | Google Scholar
N. Omura, C. P. Li, A. Li et al., “Genome-wide profiling of methylated promoters in pancreatic adenocarcinoma,” Cancer Biology and Therapy, vol. 7, no. 7, pp. 1146–1156, 2008.
View at: Google Scholar
A. C. Tan, A. Jimeno, S. H. Lin et al., “Characterizing DNA methylation patterns in pancreatic cancer genome,” Molecular Oncology, vol. 3, no. 5-6, pp. 425–438, 2009.
View at: Publisher Site | Google Scholar
A. Misawa, J. Inoue, Y. Sugino et al., “Methylation-associated silencing of the nuclear receptor 1I2 gene in advanced-type neuroblastomas, identified by bacterial artificial chromosome array-based methylated CpG island amplification,” Cancer Research, vol. 65, no. 22, pp. 10233–10242, 2005.
View at: Publisher Site | Google Scholar
Y. Sugino, A. Misawa, J. Inoue et al., “Epigenetic silencing of prostaglandin E receptor 2 (PTGER2) is associated with progression of neuroblastomas,” Oncogene, vol. 26, no. 53, pp. 7401–7413, 2007.
View at: Publisher Site | Google Scholar
K. Tanaka, I. Imoto, J. Inoue et al., “Frequent methylation-associated silencing of a candidate tumor-suppressor, CRABP1, in esophageal squamous-cell carcinoma,” Oncogene, vol. 26, no. 44, pp. 6456–6468, 2007.
View at: Publisher Site | Google Scholar
N. Nishiyama, E. Arai, Y. Chihara et al., “Genome-wide DNA methylation profiles in urothelial carcinomas and urothelia at the precancerous stage,” Cancer Science, vol. 101, no. 1, pp. 231–240, 2010.
View at: Publisher Site | Google Scholar
E. Arai and Y. Kanai, “DNA methylation profiles in precancerous tissue and cancers: carcinogenetic risk estimation and prognostication based on DNA methylation status,” Epigenomics, vol. 2, no. 3, pp. 467–481, 2010.
View at: Publisher Site | Google Scholar
J. Inazawa, J. Inoue, and I. Imoto, “Comparative genomic hybridization (CGH)-arrays pave the way for identification of novel cancer-related genes,” Cancer Science, vol. 95, no. 7, pp. 559–563, 2004.
View at: Publisher Site | Google Scholar
E. Arai, S. Ushijima, H. Fujimoto et al., “Genome-wide DNA methylation profiles in both precancerous conditions and clear cell renal cell carcinomas are correlated with malignant potential and patient outcome,” Carcinogenesis, vol. 30, no. 2, pp. 214–221, 2009.
View at: Publisher Site | Google Scholar
E. Arai, S. Ushijima, M. Gotoh et al., “Genome-wide DNA methylation profiles in liver tissue at the precancerous stage and in hepatocellular carcinoma,” International Journal of Cancer, vol. 125, no. 12, pp. 2854–2862, 2009.
View at: Publisher Site | Google Scholar
S. B. Edge, D. R. Byrd, C. C. Compton, A. G. Fritz, F. L. Greene, and A. Trotti, Eds., Exocrine and Endocrine Pancreas, Springer, New York, NY, USA, AJCC Cancer Staging Manual Seventh edition, 2010.
S. S. Han, J. Y. Jang, S. W. Kim, W. H. Kim, K. U. Lee, and Y. H. Park, “Analysis of long-term survivors after surgical resection for pancreatic cancer,” Pancreas, vol. 32, no. 3, pp. 271–275, 2006.
View at: Publisher Site | Google Scholar
T. Schnelldorfer, A. L. Ware, M. G. Sarr et al., “Long-term survival after pancreatoduodenectomy for pancreatic adenocarcinoma: is cure possible?” Annals of Surgery, vol. 247, no. 3, pp. 456–462, 2008.
View at: Google Scholar
A. van den broeck, G. Sergeant, N. Ectors, W. van Steenbergen, R. Aerts, and B. Topal, “Patterns of recurrence after curative resection of pancreatic ductal adenocarcinoma,” European Journal of Surgical Oncology, vol. 35, no. 6, pp. 600–604, 2009.
View at: Publisher Site | Google Scholar
J. Fatima, T. Schnelldorfer, J. Barton et al., “Pancreatoduodenectomy for ductal adenocarcinoma: implications of positive margin on survival,” Archives of Surgery, vol. 145, no. 2, pp. 167–172, 2010.
View at: Publisher Site | Google Scholar
K. Shimada, Y. Sakamoto, S. Nara, M. Esaki, T. Kosuge, and N. Hiraoka, “Analysis of 5-year survivors after a macroscopic curative pancreatectomy for invasive ductal adenocarcinoma,” World Journal of Surgery, vol. 34, no. 8, pp. 1908–1915, 2010.
View at: Publisher Site | Google Scholar
A. B. Lowenfels and P. Maisonneuve, “Epidemiology and prevention of pancreatic cancer,” Japanese Journal of Clinical Oncology, vol. 34, no. 5, pp. 238–244, 2004.
View at: Publisher Site | Google Scholar
M. Loos, J. Kleeff, H. Friess, and M. W. Büchler, “Surgical treatment of pancreatic cancer,” Annals of the New York Academy of Sciences, vol. 1138, pp. 169–180, 2008.
View at: Publisher Site | Google Scholar
S. J. Clark, “Action at a distance: epigenetic silencing of large chromosomal regions in carcinogenesis,” Human Molecular Genetics, vol. 16, no. 1, pp. R88–R95, 2007.
View at: Publisher Site | Google Scholar
X. G. Ni, X. F. Bai, Y. L. Mao et al., “The clinical value of serum CEA, CA19-9, and CA242 in the diagnosis and prognosis of pancreatic cancer,” European Journal of Surgical Oncology, vol. 31, no. 2, pp. 164–169, 2005.
View at: Publisher Site | Google Scholar
H. Ueno, T. Kosuge, Y. Matsuyama et al., “A randomised phase III trial comparing gemcitabine with surgery-only in patients with resected pancreatic cancer: Japanese Study Group of Adjuvant Therapy for Pancreatic Cancer,” British Journal of Cancer, vol. 101, no. 6, pp. 908–915, 2009.
View at: Publisher Site | Google Scholar
H. Ueno and T. Kosuge, “Adjuvant treatments for resectable pancreatic cancer,” Journal of Hepato-Biliary-Pancreatic Surgery, vol. 15, no. 5, pp. 468–472, 2008.
View at: Publisher Site | Google Scholar

Copyright

Copyright © 2011 Masahiro Gotoh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

PDF Download Citation

Download other formats

Order printed copies

Views

1051

Downloads

1150

Citations