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Clinical Cancer Research 14, 3354, June 1, 2008. doi: 10.1158/1078-0432.CCR-07-4609
© 2008 American Association for Cancer Research
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Imaging, Diagnosis, Prognosis

Aneuploidy Predicts Outcome in Patients with Endometrial Carcinoma and Is Related to Lack of CDH13 Hypermethylation

Yutaka Suehiro1, Toshiyuki Okada1, Takae Okada2, Keiko Anno3, Naoko Okayama1, Koji Ueno1, Mikako Hiura1, Mikiko Nakamura1, Tomoko Kondo2, Atsunori Oga2, Shigeto Kawauchi2, Kei Hirabayashi4, Fumitaka Numa4, Takehisa Ito4, Toshiaki Saito5, Kohsuke Sasaki2 and Yuji Hinoda1

Authors' Affiliations: Departments of 1 Laboratory Medicine, 2 Pathology, and 3 Obstetrics and Gynecology, Yamaguchi University Graduate School of Medicine; 4 Department of Obstetrics and Gynecology, Tokuyama Central Hospital, Yamaguchi, Japan; and 5 Department of Gynecology, National Kyushu Cancer Center, Fukuoka, Japan

Requests for reprints: Yutaka Suehiro, Department of Laboratory Medicine, Yamaguchi University Graduate School of Medicine, Ube, Yamaguchi 755-8505, Japan. Phone: 81-836-22-2337; Fax: 81-836-22-2338; E-mail: ysuehiro{at}yamaguchi-u.ac.jp.


   Abstract
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 Abstract
Materials and Methods
 Results
 Discussion
 Disclosure of Potential...
 References
 
Purpose: Many investigators have reported that aneuploidy detected by flow cytometry is a useful prognostic marker in patients with endometrial cancer. Laser scanning cytometry (LSC) is a technology similar to flow cytometry but is more feasible for clinical laboratory use. We evaluated the usefulness of DNA ploidy detected by LSC as a prognostic marker in patients with endometrial cancer and investigated genetic and epigenetic factors related to aneuploidy.

Experimental Design: Endometrial cancer specimens from 106 patients were evaluated. The methylation status of CDH13, Rassf1, SFRP1, SFRP2, SFRP4, SFRP5, p16, hMLH1, MGMT, APC, ATM, and WIF1 and mutations in the p53 and CDC4 genes were investigated. LSC was carried out to determine DNA ploidy. Fluorescence in situ hybridization was done with chromosome-specific centromeric probes to assess chromosomal instability.

Results: Univariate and multivariate analyses revealed that p53 mutation and lack of CDH13 hypermethylation associated positively with aneuploidy. Univariate analysis showed that aneuploidy, chromosomal instability, and lack of CDH13 hypermethylation as well as surgical stage were significantly predictive of death from endometrial cancer. Furthermore, multivariate analysis revealed that stage in combination with either DNA aneuploidy or lack of CDH13 hypermethylation was an independent prognostic factor.

Conclusion: These results suggest that analysis of DNA ploidy and methylation status of CDH13 may help predict clinical outcome in patients with endometrial cancer. Prospective randomized trials are needed to confirm the validity of an individualized approach, including determination of tumor ploidy and methylation status of CDH13, to management of endometrial cancer patients.

Endometrial cancer is one of the most common genital cancers in women worldwide. The highest incidences are observed in western Europe and North America (1), whereas the incidence is lower but rapidly rising in Japan (1, 2). The number of endometrial cancer patients in Japan was estimated as 1.5 to 1.7 per 100,000 women in the 1970s; however, it has been steadily increasing and is now estimated as 6 to 7 cases per 100,000 women in the 2000s (2). Changes in diet and lifestyle related to obesity, a risk factor for endometrial cancer (3), may account for the drastic increase in endometrial cancer in Japan.

Surgical stage is used routinely to guide patient treatment. Histologic grade is also used because the prognosis for low-grade endometrial cancers is better than for high-grade endometrial cancers (4). Improved tumor classification is needed, however, because patients with tumors that are identical in grade and stage often have significantly different clinical outcomes or responses to therapy. In previous studies, flow cytometric analysis of DNA ploidy has been shown to provide stronger, independent prognostic information (5–10). Laser scanning cytometry (LSC) is a technology similar to flow cytometry, but LSC generates data from analysis of successive microscopic fields and is advantageous for certain clinical and research applications (11). In general, the advantages of LSC include reduced specimen size requirements, simplified methodologies, the ability to examine individual cells, microscopically allowing for direct comparison between cytologic morphology and objective fluorescence measurements, and the ability to scan the same cells within an individual specimen repeatedly (11). Although LSC seems more suitable for clinical application, the relation between DNA ploidy detected by LSC and the clinicopathologic features in patients with endometrial cancer has not been studied.

Tumor cells can become aneuploid as a result of aberrant mitotic divisions that are caused by errors in centrosome duplication, chromosome cohesion, spindle attachment, or cytokinesis (12). Mitotic checkpoint defects lead to aneuploidy in cultured cells (13) and mouse models (14). However, mutations of such mitotic checkpoint genes have been detected in only a fraction of human cancers (15). This prompted us to speculate that multiple factors, such as DNA methylation and chromatin modification, are key players in tumor cell aneuploidization.

In the present study, we evaluated the efficacy of DNA ploidy determined by LSC as a prognostic marker in patients with endometrial cancer and investigated clinicopathologic, genetic, and epigenetic factors related to aneuploidy and patient outcomes. We found that aneuploidy and lack of CDH13 hypermethylation as well as surgical stage were predictive of death from endometrial cancer and that age, p53 mutation, and lack of CDH13 hypermethylation were related to aneuploidy.


   Materials and Methods
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 Abstract
 Materials and Methods
Results
 Discussion
 Disclosure of Potential...
 References
 
Specimens. We evaluated endometrial cancer specimens from 106 patients who underwent surgical resection of the uterus. Mean age of the patients was 58.0 y (range, 32-81 y). Mean follow-up time was 34.8 mo (range, 3.2-89.4 mo). Stage, grade, and histologic type were determined with the surgical staging system of the International Federation of Gynecology and Obstetrics (1988) and WHO (1994). All tumors were diagnosed histologically as endometrioid carcinomas of the uterine corpus and included 94 endometrioid adenocarcinomas, 10 adenoacanthomas, and 2 adenosquamous carcinomas. No patient received preoperative neoadjuvant therapy. Normal endometrium was obtained from 27 patients with leiomyoma who underwent hysterectomy. The study was approved by the review board of Yamaguchi University.

Microdissection and DNA extraction. Routine frozen resection specimens were fixed in 99.5% ethanol followed by H&E staining. DNA was prepared from 5-µm microdissected histopathologic sections as described previously (16).

Hypermethylation of genes. Hypermethylation of CDH13 and Rassf1 is frequent in endometrial cancer (17). However, association of methylation of CDH13 and Rassf1 with clinicopathologic and cytogenetic features in endometrial cancer has not been clarified. This challenged us to investigate the relations. Furthermore, some of endometrial cancers and colon cancers have a common molecular feature such as microsatellite instability via hMLH1 methylation (18–20). This promoted us to study hMLH1 methylation status in endometrial cancer followed by methylation of other genes, including p16, SFRP1, SFRP2, SFRP4, SFRP5, WIF1, APC, ATM, and MGMT, which are methylated frequently in colon cancer (21–26).

The methylation status of Rassf1, SFRP1, SFRP2, SFRP4, SFRP5, p16, hMLH1, MGMT, ATM, and APC was determined by bisulfite treatment of DNA followed by methylation-specific PCR or combined bisulfite restriction analysis as described previously (21–25, 27).

WIF1 methylation-specific PCR primers for the methylation reaction were 5'-CGTTTTATTGGGCGTATC-3' (forward) and 5'-CGAAACCAACAATCAACG-3' (reverse) and for the unmethylation reaction were 5'-GGGTGTTTTATTGGGTGTATT-3' (forward) and 5'-CTAACAAAACCAACAATCAACA-3' (reverse; Supplementary Fig. S1).

Methylation status of CDH13 was assessed by combined bisulfite restriction analysis assay. Primer sequences were 5'-TTTAAAGAAGTAAATGGGATGTT-3' and 5'-CCAAAACCAATAACTTTACAAA-3'. The PCR product was digested with NruI (TaKaRa). The digested PCR products were separated by electrophoresis on 3% agarose gels. The digested fragments, which represent methylated DNA, were quantitated by densitometry.

DNA from normal lymphocytes was used as the control for unmethylated genes and placental DNA treated with SssI (CpG) methylase (New England Biolabs) was used as the positive control for methylated genes. Each sample was analyzed in duplicate. The criterion for the presence of hypermethylation was detection of a methylated band in both independent methylation-specific PCR assays. In combined bisulfite restriction analysis assay, hypermethylation was defined as ≥14% of methylation for CDH13 and ≥9% of methylation for Rassf1 on the bases of upper 95% of mean methylation level of each gene in normal endometrium.

Assay for p53 and CDC4 mutations. DNA sequencing was used to screen for mutations in the p53 and CDC4 genes. For p53, four sets of oligonucleotide primers were used to amplify exons 5 to 8 as described previously (Supplementary Table S1; ref. 28).

For CDC4, 10 sets of oligonucleotide primers were used to amplify exons 2 to 11 (Supplementary Table S1). PCR products were purified with shrimp alkaline phosphatase and exonuclease I (GE Healthcare) per the manufacturer's instructions. Purified PCR products were sequenced on an ABI Prism 3100 DNA Analyzer with the ABI Prism BigDye Terminator Cycle Sequencing kit version 3.1 (Applied Biosystems). Primers used for amplification were also used for sequencing. Sequencing results were analyzed with DNA Sequencing Analysis Software version 5.1 (Applied Biosystems) and Mutation Surveyor (SoftGenetics).

Fluorescence in situ hybridization analysis. Fluorescence in situ hybridization was carried out on touch smear specimens on cell array glass slides with chromosome-specific centromeric probes for chromosomes 7, 8, 10, 11, and 17 (Abbott Molecular) as described previously (29). Briefly, the DNA probe mixture and 10 µg of Cot-1 DNA (Abbott Molecular) were dissolved in hybridization buffer (Abbott Molecular). The probe mixture was denatured at 73°C for 5 min, applied to the denatured touch smears, and incubated in a moist chamber at 37°C overnight. After the slide was rinsed, nuclei were counterstained with 4',6-diamidino-2-phenylindole II (Abbott Molecular). The number of nuclear hybridization signals was determined for 100 nuclei from each sample. The variant fraction was defined as the fraction of cells for which the chromosome number differed from the modal chromosome number (30). Unstable chromosomes were tentatively defined as >20% of the average variant fractions of chromosomes 7, 8, 10, 11, and 17, with reference to Lengauer et al. (31) and Yamamoto et al. (32). A tumor was considered to have chromosomal instability (CIN) if the tumor was unstable for more than three chromosomes as described previously (29).

Laser scanning cytometry. LSC was carried out to determine DNA ploidy as described previously (29). Briefly, touch smears fixed with 95% ethanol were stained in 25 µg/mL propidium iodide solution containing 0.1% RNase. A coverslip was put on the slide and sealed with nail polish. DNA content was measured with a laser scanning cytometer (LSC101, Olympus). A DNA histogram was generated, and DNA ploidy was determined. The DNA index was calculated according to published principles (33). Tumors with a DNA index ≤1.2 were categorized as diploid tumors, and those with a DNA index >1.2 were classified as aneuploid tumors (29).

Statistical analysis. Statistical analysis was done with StatView statistical software (SAS). To compare variables, Fisher's exact test, Student's t test, and logistic regression method were used. A P value of <0.05 was considered statistically significant. To identify potential distinct subgroups among endometrial cancer patients, we applied an unsupervised hierarchical cluster analysis based on methylation profiling of CDH13 and Rassf1, aneuploidy, and CIN using Euclidean distances and average linkage algorithm (Clustered Image Map program package, CIMminer;6 ref. 34).


   Results
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 Abstract
 Materials and Methods
 Results
Discussion
 Disclosure of Potential...
 References
 
Methylation and mutation profile. Clinicopathologic features, gene hypermethylation, gene mutation, aneuploidy, and CIN profiles in 106 endometrial cancers are shown in Fig. 1 . The frequencies of gene hypermethylation in normal endometrium and endometrial cancer are shown in Table 1 . Hypermethylation of CDH13 and Rassf1 was observed frequently in endometrial cancer (70.8% and 82.5%, respectively) as described previously (17). The quantitative analysis of CDH13 methylation showed that endometrial cancer had higher levels of CDH13 methylation than normal endometrium (Fig. 2A ). The mean methylation level was 40.3% for endometrial cancer and 7.1% for the normal endometrium (P < 0.0001). Mean methylation level of Rassf1 was also greater in endometrial cancer than in normal endometrium (62.3% versus 4.6%; P < 0.0001; Fig. 2B). These data suggest that detection of CDH13 and Rassf1 methylation using cytologic materials may be useful as a screening test for endometrial cancer as reported previously (17).


Figure 1
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  		Fig. 1. Diagram of clinicopathologic, epigenetic, and genetic alterations in 106 endometrial cancers. Shading indicates the presence of a molecular alteration, x indicates unavailable data, and an open cell indicates absence of the alteration.

 

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  		Table 1. Frequency of hypermethylation of genes in normal endometrium and endometrial cancer

 

Figure 2
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  		Fig. 2. Distribution of CDH13 and Rassf1 methylation (%) in normal endometrium and endometrial cancer. The horizontal lines represent the mean methylation level in each group.

 
p53 and CDC4 mutation were observed in 21 of 104 (20.2%) and 5 of 60 (8.3%) endometrial cancers, respectively. Aneuploidy and CIN were found in 19 of 106 (17.9%) and 16 of 106 (15.1%) endometrial cancers, respectively.

Comparison of gene methylation, p53 mutations, and CDC4 mutations with aneuploidy and CIN. Aneuploidy and CIN were highly concordant with an expected relation in 91.4% of the carcinomas (P < 0.0001) as reported previously (29). Thirteen of 19 (68.4%) cases with aneuploidy had CIN, whereas 84 of 87 (96.6%) cases without aneuploidy did not have CIN [odds ratio (OR), 60.7; 95% confidence interval (95% CI), 13.5-273.1; P < 0.0001].

Association between various factors, including clinicopathologic variables, gene hypermethylation, and gene mutation, and the presence of aneuploidy is shown in Table 2 . In addition, these factors were also compared with CIN for validation (Table 2). Hypermethylation of CDH13 was shown to have an inverse association with aneuploidy and CIN. In other words, lack of CDH13 hypermethylation associated positively with aneuploidy and CIN. Only 7 of 75 (9.3%) tumors with CDH13 hypermethylation had aneuploidy, whereas 12 of 31 (38.7%) tumors without CDH13 hypermethylation had aneuploidy (P = 0.0007). Similarly, 7 of 75 (9.3%) tumors with CDH13 hypermethylation had CIN, whereas 9 of 31 (29.0%) tumors without CDH13 hypermethylation showed CIN (P = 0.0160). p53 mutation related positively with aneuploidy and CIN. Eleven of 21 (52.4%) tumors with p53 mutations had aneuploidy, whereas 8 of 83 (9.6%) cases without p53 mutations had aneuploidy (P < 0.0001). In addition, 9 of 21 (42.9%) tumors with p53 mutations had CIN, whereas only 6 of 83 (7.2%) cases without p53 mutations had CIN (P = 0.0003). Mean age was significantly higher in cases with aneuploidy and CIN than in those without. Mean age was 62.0 years for cases with aneuploidy and 57.1 years for cases without aneuploidy (P = 0.0448) and 63.8 years for cases with CIN and 56.9 years for cases without CIN (P = 0.0074). According to multivariate analysis, lack of CDH13 hypermethylation and p53 mutation related positively to aneuploidy (Table 3 ). Similarly, age, lack of CDH13 hypermethylation, and p53 mutation were associated significantly with CIN (Table 3).


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  		Table 2. Aneuploidy and CIN in relation to clinicopathologic features, hypermethylation of genes, and mutation of genes

 

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  		Table 3. Results of multivariate analysis of risk factors for aneuploidy and CIN in patients with endometrial cancer

 
We also studied correlations between methylated genes in endometrial cancer (Supplementary Table S2). Five markers, including hMLH1, and four genes (CHFR, WIF1, Rassf1, and SFRP4), which were methylated concurrently with hMLH1 methylation, were used to determine methylation phenotype. Endometrial cancer was classified as having methylator phenotype if 50% or more of the evaluated markers were methylated. Relation of the methylator phenotype with aneuploidy, CIN, and p53 mutation was shown in Supplementary Table S3. Interestingly, the methylator phenotype correlated negatively with CIN in endometrial cancer, as shown for colon cancer (35). None of 16 (0.0%) cancers with CIN has methylator phenotype, whereas 26 of 90 (28.9%) cancers without CIN have methylator phenotype (P = 0.0105).

Risk factors for nonsurvival. Results of univariate analysis of risk factors for nonsurvival are shown in Table 4 . Regardless of differences in follow-up time, variables including stages III and IV, CIN, and aneuploidy related significantly to death from the disease (P = 0.0451, 0.0296, 0.0280, and 0.0120, respectively). In addition, CDH13 hypermethylation associated negatively with unfavorable outcome (P = 0.0143). In other words, lack of CDH13 hypermethylation was associated with negative prognosis. Age of the patients did not correlate with death from endometrial cancer. Mean age of the patients who died was 61.6 years; mean age of patients who survived was 57.2 years (P = 0.1851).


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  		Table 4. Univariate analysis of risk factors for nonsurvival

 
Multivariate analysis showed that the stage in combination with either DNA aneuploid type or lack of CDH13 hypermethylation was significantly predictive of death from the disease (Table 5A and B ). However, CIN and Rassf1 methylation were not independent prognostic markers (data not shown).


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  		Table 5. Results of multivariate analysis of risk factors for nonsurvival in patients with endometrial cancer

 
Based on the hierarchical clustering result, we estimated the number of clusters at 2 (Supplementary Fig. S2). The cluster 2 related significantly to death from the disease. Frequency of nonsurviving patients was 4 of 75 (5.3%) for the cluster 1, whereas it was 5 of 17 (29.4%) for the cluster 2 (OR, 7.4; 95% CI, 1.7-31.5; P = 0.0097).


   Discussion
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 Materials and Methods
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In the current study, we found that aneuploidy was a useful prognostic marker in patients with endometrial cancer, which is consistent with the results of previous studies (5–10). Interestingly, DNA aneuploidy was associated with increased mortality even for stage I endometrial cancer (5, 10). Furthermore, Susini et al. (9) have reported results of a 10-year prospective study in which the presence of aneuploidy in endometrial cancer identified high-risk cases among patients considered to be at ‘low risk’ based on stage and grade of differentiation. Thus, DNA aneuploidy can be a useful prognostic marker in patients with endometrial cancer. Although our finding is not new, this is the first study that evaluated the usefulness of laser scanning cytometric DNA analysis for predicting patient outcomes. The utility of flow cytometric measurements of DNA ploidy in various carcinomas remains controversial (36). Retrospective studies of large numbers of patients and the exchange of samples among laboratories are hampered by the relative scarcity of archival frozen material and difficulties in transporting frozen specimens (37). However, LSC can resolve these problems. Touch preparations for LSC require only small amounts of fresh material (11) and can be stored and transported at 4°C or even at room temperature. Furthermore, another advantage of LSC is that cells selected visually can be quantified. Conversely, cells selected by LSC measurement can be relocated and examined visually. This is important for analyzing cellular properties of malignant tumors because contamination with normal cells is inevitable. Thus, LSC seems more feasible for clinical laboratory use than flow cytometry. Further studies with larger sample sizes and multiple laboratory groups are needed to confirm the feasibility of laser scanning cytometric DNA analysis as a clinical laboratory test.

We found that lack of CDH13 hypermethylation is positively associated with aneuploidy, CIN, and an unfavorable outcome. Evaluation of methylation level of CDH13 may assist in therapeutic decision for patients with endometrial cancer. To our knowledge, ours is the first report on the relation of lack of CDH13 hypermethylation to aneuploidy, CIN, and death from endometrial cancer. CDH13 (also known as H-cadherin or T-cadherin) is an atypical glycosylphosphatidylinositol-anchored member of the cadherin superfamily (38). Down-regulation of CDH13 gene expression related to promoter hypermethylation has been reported frequently for breast, lung, and colon carcinomas (39, 40). In contrast, in primary hepatocellular carcinomas, CDH13 is globally overexpressed in approximately half of all tumor specimens (38). Although CDH13 can mediate weak homophilic cell-cell aggregation (41), accumulating evidence suggests that CDH13 might not function as a true intercellular adhesion molecule (42, 43). Because the function of CDH13 is not yet known, further studies are needed.

Aneuploidy, a state of abnormal chromosome number and content, is characteristic of many human cancers, and it plays an important role in tumor formation and development (44). Genetic change leading to aneuploidy is termed CIN, which is defined by continuous and conspicuous changes in chromosome structure and number (45). It is well known that CIN is associated with aneuploidy (29, 30, 46). It is also widely accepted that tumor cells become aneuploid as a result of aberrant mitotic divisions that are caused by errors in centrosome duplication, chromosome cohesion, spindle attachment, or cytokinesis (12). Indeed, mitotic checkpoint defects lead to aneuploidy in cultured cells (13) and mouse models (14). However, mutations of such mitotic checkpoint genes have been detected in only a fraction of human cancers (15). This prompted us to speculate that multiple factors, such as DNA methylation and chromatin modification, are key players in tumor cell aneuploidization. Several studies have shown a possible association between DNA methylation status and CIN in cancer cells. For example, hypomethylation of pericentromeric satellite sequences predisposes to chromosomal breakage and recombination, leading CIN in tumor cells (47, 48). Interestingly, CDH13 hypomethylation is associated with satellite DNA hypomethylation in ovarian and breast cancers (49, 50). Thus, lack of CDH13 hypermethylation may be a predictive marker for aneuploidy via satellite DNA hypomethylation.

We found that mutation of p53 is related to aneuploidy and CIN as found in previous studies (9). Normal p53 function imposes a barrier to genomically unstable cells by stimulating G1-S or G2-M checkpoint responses, mitotic catastrophe, and apoptotic cell death (51). In contrast, cells with inactivated p53 may overcome these barriers and maintain proliferative activity despite CIN (52). The most frequent form of genomic instability in human cancer, aneuploidy, often coincides with loss of p53. However, there is mounting evidence that a defect in p53 does not have a direct role in CIN but instead promotes CIN indirectly (52–54). In addition, the present finding that p53 mutation correlates with aneuploidy and CIN but not patient outcomes suggests that p53 mutation alone may be only an early event in the CIN pathway and have little effect on the malignant behavior of tumor cells.

In the current study, CDC4 mutations were not associated with aneuploidy or CIN. Rajagopalan et al. (55) reported that CDC4 (F-box and WD40 domain protein 7, FBW7, FBXW7) is a CIN gene for human cancer. However, the association between CDC4 mutation and CIN is controversial. Hubalek et al. (56) screened for CDC4 mutations in endometrial cancers. When they excluded isoform-specific changes, they found mutations in 6 of 12 aneuploid and/or polyploid cancers and in none of 3 diploid lesions. Although these data were suggestive of a link between CDC4 mutations and CIN, the association was not statistically significant (P = 0.19, Fisher's exact test). Furthermore, Kemp et al. (57) screened 244 colorectal tumors and 40 cell lines for CDC4 mutations and CIN. They found that 18 of 284 (6%) tumors, including near-diploid (CIN–) lesions, harbored CDC4 mutations and that there was no association between CDC4 mutations and CIN. These results suggest that CDC4 mutations are not associated with CIN.

In conclusion, we found a significant relation between DNA aneuploidy and lack of CDH13 hypermethylation in endometrial cancer. Furthermore, we observed a significant association of DNA aneuploidy and lack of CDH13 hypermethylation with negative prognosis. The validity of an individualized approach to management of endometrial cancer patients, including determination of tumor ploidy and CDH13 methylation status, should be properly evaluated in prospective randomized trials.


   Disclosure of Potential Conflicts of Interest
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The authors declare that there is no conflict of interest.


   Footnotes
 
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.

6 http://discover.nci.nih.gov Back

Received 10/11/07; revised 1/28/08; accepted 2/26/08.


   References
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 Disclosure of Potential...
 References
 

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