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Cancer Research 68, 4597, June 15, 2008. doi: 10.1158/0008-5472.CAN-07-6645
© 2008 American Association for Cancer Research
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Molecular Biology, Pathobiology, and Genetics

Epigenetic Signatures of Familial Cancer Are Characteristic of Tumor Type and Family Category

Emmi I. Joensuu1, Wael M. Abdel-Rahman1, Miina Ollikainen1, Salla Ruosaari2,3,4, Sakari Knuutila3 and Päivi Peltomäki1

1 Department of Medical Genetics, University of Helsinki; 2 Health and Work Ability, Biological Mechanisms and Prevention of Work-Related Diseases, Finnish Institute of Occupational Health; 3 Department of Pathology, Haartman Institute and HUSLAB, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland; and 4 Helsinki Institute for Information Technology, Laboratory of Computer and Information Science, Helsinki University of Technology, Espoo, Finland

Requests for reprints: Emmi I. Joensuu, Department of Medical Genetics, Biomedicum Helsinki, University of Helsinki, P. O. Box 63, FIN-00014 Helsinki, Finland. Phone: 358-919125189; Fax: 358-919125105; E-mail: emmi.joensuu{at}helsinki.fi.


   Abstract
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 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 Disclosure of Potential...
 References
 
Tumor suppressor genes (TSG) may be inactivated by methylation of critical CpG sites in their promoter regions, providing targets for early detection and prevention. Although sporadic cancers, especially colorectal carcinoma (CRC), have been characterized for epigenetic changes extensively, such information in familial/hereditary cancer is limited. We studied 108 CRCs and 63 endometrial carcinomas (EC) occurring as part of hereditary nonpolyposis CRC, as separate familial site-specific entities or sporadically, for promoter methylation of 24 TSGs. Eleven genes in CRC and 6 in EC were methylated in at least 15% of tumors and together accounted for 89% and 82% of promoter methylation events in CRC and EC, respectively. Some genes (e.g., CDH13, APC, GSTP1, and TIMP3) showed frequent methylation in both cancers, whereas promoter methylation of ESR1, CHFR, and RARB was typical of CRC and that of RASSF1(A) characterized EC. Among CRCs, sets of genes with methylation characteristic of familial versus sporadic tumors appeared. A TSG methylator phenotype (methylation of at least 5 of 24 genes) occurred in 37% of CRC and 18% of EC (P = 0.013), and the presence versus absence of MLH1 methylation divided the tumors into high versus low methylation groups. In conclusion, inactivation of TSGs by promoter methylation followed patterns characteristic of tumor type (CRC versus EC) and family category and was strongly influenced by MLH1 promoter methylation status in all categories. Paired normal tissues or blood displayed negligible methylation arguing against a constitutional methylation abnormality in familial cases. [Cancer Res 2008;68(12):4597–605]


   Introduction
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 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 Disclosure of Potential...
 References
 
Cancer results from the sequential accumulation of mutations in critical tumor suppressor genes (TSG), oncogenes, and other genes, giving rise to genetic signatures specific to tumor type and each individual tumor (1). Parallel epigenetic changes involving, for example, DNA methylation or histone modification may occur from the earliest steps of tumorigenesis (2, 3). Many TSGs are inactivated by methylation of critical CpG sites in their promoter regions (4). Promoter methylation of the DNA mismatch repair (MMR) gene MLH1 underlies most cases of sporadic colorectal carcinoma (CRC; ref. 5) or endometrial carcinoma (EC; ref. 6) with microsatellite instability (MSI) and may be part of a more generalized CpG island methylator phenotype (CIMP; ref. 7). Analysis of unselected CpG islands has revealed global alterations in DNA methylation (8). Hypomethylation may promote tumorigenesis by activating oncogenes (9) and, when present globally, by inducing chromosomal instability (10). The potential reversibility of epigenetic states offers exciting opportunities for drug development (4).

Inherited mutations in MMR genes cause susceptibility to CRC, EC, and other cancers typical of hereditary nonpolyposis CRC (HNPCC)/Lynch syndrome (11). A significant fraction of families with HNPCC-like presentation ["familial CRC type X" (FCCX)] as well as families with the sole or predominant clustering of EC ["familial site-specific EC" (FSSEC)] show no germ-line mutations in MMR genes (12, 13) and remain to be molecularly characterized. Recent observations (14–17) raise the intriguing possibility of an epigenetic basis of cancer susceptibility in such families.

We applied a newly developed technique, methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA; ref. 18), and took a candidate gene approach to investigate 24 TSGs for promoter methylation in a large series of familial and sporadic tumors. Our analysis revealed novel and nonrandom epigenetic patterns that increase the understanding of the developmental mechanisms of such cancers.


   Materials and Methods
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 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 Disclosure of Potential...
 References
 
Patients and samples. This study was performed on 162 (adenocarcinoma) tumor samples, CRC or EC, from familial and sporadic cases (Table 1 ) as well as on 9 cell lines (Supplementary Table S4). The patients represented a nationwide registry of hereditary CRC families [HNPCC and FCCX (19)] or population-based cohorts corresponding to certain hospital districts in Finland (FSSEC and sporadic CRC). Familial CRC and EC consisted of mutation-positive and mutation-negative groups depending on the presence versus absence of germ-line mutation in MMR genes MLH1, MSH2, MSH6, or PMS2. All HNPCC individuals carried germ-line mutations of their families, whereas in FCCX and FSSEC families such mutations had been excluded (12, 13, 20). Families with adenomatous polyposis were not included.


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  		Table 1. Characteristics of tumors studied from familial and sporadic cases

 
DNA was extracted from paraffin-embedded specimens by a method modified from Isola and colleagues (21). Mutation screening, MSI analysis, and immunohistochemical (IHC) analysis were performed in previous studies (12, 13, 20, 22, 23), except for sporadic samples that were studied for MSI and IHC as part of the present study.

The appropriate institutional review boards of the Helsinki University Central Hospital approved this study.

Methylation-specific multiplex ligation-dependent probe amplification. The SALSA MS-MLPA Kit ME001 Tumor suppressor-1 (MRC-Holland) was used to study promoter methylation of 24 TSGs (Supplementary Table S5). The MS-MLPA method (18, 24) is based on probes that recognize specific sequences in DNA that contain a restriction site for a methylation-sensitive HhaI enzyme. HhaI digests unmethylated DNA from the middle of GCGC sequences but leaves methylated sites intact, generating a signal if DNA is undigested. The locations of the target HhaI sites are given in the MRC-Holland Web site.5

All MS-MLPA reactions, analyses, and calculations of methylation dosage ratios were done according to the manufacturer's instructions5 using 100 to 150 ng of DNA. The MS-MLPA products were separated by capillary electrophoresis (on ABI 3730 Automatic DNA sequencer, Applied Biosystems) and analyzed using GeneMapper4.0 genotyping software (Applied Biosystems). Methylation dosage ratio was obtained by the following calculation: Dm = (Px / Pctrl)Dig / (Px / Pctrl)Undig, where Dm is the methylation dosage ratio, Px is the peak area of a given probe, Pctrl is the sum of the peak areas of all control probes, Dig stands for HhaI digested sample, and Undig stands for undigested sample. Based on our previous validation experiments (25), a given promoter was considered to show methylation if the methylation dosage ratio was ≥0.15 (corresponding to 15% of methylated DNA).

Methylation-specific PCR. Methylation-specific PCR (MSP; ref. 26) was performed using previously published primers to amplify either methylated or unmethylated alleles from the promoter regions of MLH1 (27), RASSF1(A) (28), and APC (promoter A1; ref. 29). DNA (1 µg) was modified with sodium bisulfite treatment (CpGenome DNA Modification kit, Chemicon) and subjected to MSP. MSP was performed in a volume of 25 µL containing 24 ng of bisulfite-modified template per reaction with HotStarTaq DNA polymerase (Qiagen). Cycling conditions were according to the manufacturers' standard cycling protocol for HotStarTaq DNA polymerase, with 36 cycles for MLH1 and RASSF1(A) and 38 to 42 cycles for APC. Annealing temperatures were 55°C for methylated reaction and 57°C for unmethylated reaction for MLH1, 64°C for methylated reaction and 59°C for unmethylated reaction for RASSF1(A), and 60°C for both methylated and unmethylated reactions for APC. MSP products were run through a 2% agarose gel, stained with ethidium bromide, and visualized with UV transillumination. All sodium bisulfite modifications and MSP runs were repeated at least twice. A negative control without template was included in each MSP run.

mRNA expression analysis by microarrays. We took advantage of microarray data generated for another study6 and the related information is to be published in more detail elsewhere. Analyses were done using HG-U133 Plus 2.0 array (Affymetrix). The protocols for HG-U133 Plus 2.0 arrays were as described by the manufacturer (Affymetrix). Briefly, total RNA was extracted from cell lines by RNeasy (Qiagen). Aliquot of each RNA sample was run on a 2100 Bioanalyzer (Agilent Technologies) to visualize and quantify the degree of RNA integrity. Double-stranded cDNA was synthesized from 5 µg of total RNA using the GeneChip One-Cycle cDNA Synthesis kit followed by cleanup with GeneChip Sample Cleanup Module, in vitro transcription (IVT), and Biotin labeling reaction using the GeneChip IVT Labeling kit, and cleanup and quantification of the biotin-labeled cRNA yield by spectrophotometric analysis. All kits were from Affymetrix. Fragmentation of the cRNA and hybridizations to test chips and to the HG-U133 Plus 2.0 array were done according to Affymetrix protocols, and microarrays were processed by the Affymetrix Fluidics Station 450 and scanned with an Affymetrix GeneChip Scanner 7G. Captured images were analyzed using Microarray Suite version 5.0 algorithm (Affymetrix). All quality control criteria recommended by Affymetrix were observed in the "test" chips and sample chips.

The hybridization data were preprocessed using robust multiarray average (RMA; ref. 30), designed to enhance the comparability of expression measures between separate arrays. RMA preprocessing produces a single expression measure for each probe set in the Affymetrix array, which can be readily used in subsequent analyses. As duplicate arrays were available for each cell line, the median of the two RMA values was used as the expression value. Gene assignments of the probes were extracted from the Affymetrix annotation files and genes with ambiguous information about the physical location were excluded from the analyses.

Statistical analysis. Statistical significance between groups was determined with t test for independent or correlated samples or with Fisher's exact probability test. P values of <0.05 (two tailed) were considered significant.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 Disclosure of Potential...
 References
 
Validation of MS-MLPA. MS-MLPA was validated for methylation patterns by MSP using cell lines (Supplementary Table S4). We chose three loci, MLH1, APC, and RASSF1(A), which represented known methylation targets in cancer, resulting in silencing of the respective genes (4). Positions of the studied HhaI sites (MS-MLPA) relative to the first nucleotide of the initiating ATG (Genbank accession number in parentheses) were –6 for MLH1 (U26559), –17053 for APC (U02509), and –85 and –136 for RASSF1 (NM_007182) and Castanotto and colleagues (31). Regions studied by MSP were close to these sites (see Materials and Methods). Methylation results were fully concordant between MSP and MS-MLPA (Fig. 1 ).


Figure 1
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  		Figure 1. Promoter CpG island methylation analysis by MSP (A) and MS-MLPA (B) of EC (HEC59) and CRC (HCA7 and RKO) cell lines. A, gel electrophoresis after MSP showing a product for either the methylated (M) or unmethylated (U) reaction, except for APC in HCA7 with visible products in both methylated and unmethylated lanes. B, analysis of the same samples by MS-MLPA where the position on the X axis identifies the exact gene or promoter, and area (height) for a given peak is proportional to the degree of methylation across samples. In agreement with MSP, MS-MLPA showed either biallelic methylation or complete lack of methylation (methylation ratios close to 100% or 0%, respectively) with the exception of HCA7 with monoallelic methylation (50%) of APC.

 
Microarray-based mRNA analysis was conducted to verify that methylation of the exact CpG sites addressed by MS-MLPA was associated with gene silencing. Methylation by MS-MLPA correlated with reduced or absent expression by microarray analysis, as best evident for TIMP3, MLH1, RARB, CHFR, IGSF4, CDH13, and GSTP1 (Supplementary Table S6).

The present MLH1 methylation data were also validated against IHC results of the patient specimens (refs. 13, 22, 23 and this study). With one exception (a FSSEC tumor), MLH1 protein expression was down-regulated whenever MLH1 promoter was methylated. Our MS-MLPA assay monitored "area D" whose methylation was reported to correlate with MLH1 protein expression by Deng and colleagues (32).

Overall frequencies for promoter methylation. The present 24 TSGs (see Supplementary Table S5 for a description) were chosen because their inactivation has been shown to play a role in a wide variety of human cancers (4, 33). MS-MLPA was performed on 162 clinical tumor specimens (Table 1) in addition to the cell lines described above. We focused on CRC and EC occurring sporadically, as part of HNPCC associated with germ-line mutations in MMR genes or as separate site-specific entities without detectable MMR gene germ-line mutations (FCCX and FSSEC). Based on the presence versus absence of indicators of MMR deficiency (MSI and/or aberrant MMR protein expression), HNPCC-CRC and HNPCC-EC had abnormal MMR and FCCX normal MMR as a rule, whereas FSSEC and sporadic CRC were divided into two subgroups. Using a methylation dosage ratio of 0.15 for a threshold indicating methylation [similar to Rashid and Issa (34)], an average of 4.4 TSG promoters was methylated per CRC tumor, which was significantly higher compared with EC (average, 2.7; P < 0.0001; Table 2 ). Our HNPCC series included nine patients with double cancers (CRC and EC). In additional support for the tissue-specific methylation differences, CRC and EC tumors from these patients showed a difference of borderline significance (4.9 versus 2.4 methylated genes, respectively; P = 0.053).


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  		Table 2. TSG methylation profiles in CRC and EC by tumor category and MMR status

 
The distinct clinical subcategories of CRC fell into two major groups according to the average number of methylated genes per tumor (Table 2). Sporadic CRC with normal MMR (3.5), FCCX (3.7), and HNPCC-CRC (3.9) grouped together and showed less frequent methylation of TSG loci compared with MMR-deficient CRC cell lines (6.9) and sporadic CRC with abnormal MMR (7.3). The specific EC cohorts displayed less variation, which in part reflected the generally lower proportions of methylated loci compared with CRC, with the exception of the EC cell line (6.0).

In individual tumors, the number of methylated genes ranged from 0 to 11, with the exception of a single HNPCC-CRC tumor with 18 methylated genes (Fig. 2 ). Based on the distribution of methylation among different genes (Table 2) and tumors (Figs. 2 and 3 ), promoter methylation of at least 5 of the 24 analyzed genes per tumor was considered to indicate TSG methylator phenotype. This phenotype was present in 42% of CRCs and 19% of ECs (Table 2). Excluding cell lines, 37 of 100 (37%) of CRCs and 11 of 62 (18%) of ECs (P = 0.013) displayed the phenotype, with the highest frequencies in cohorts having abnormal MMR but no germ-line mutations in MMR genes. Furthermore, a TSG methylator phenotype frequency of 50% in FCCX was interesting because of the lack of MMR deficiency and the unknown genetic etiology of this group (see further discussion below).


Figure 2
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  		Figure 2. Tumor-specific variation in the proportion of methylated genes in HNPCC (A and B) and FSSEC (C and D). Distribution of tumors according to an increasing number of methylated genes is shown. Among 24 TSGs studied, the highest number of methylated genes per tumor was 11, except for a single HNPCC-CRC tumor with 18 methylated genes (note a consequent change in the scale of X axis in A). The share of tumors with MLH1 as one of the methylated genes is indicated with darker shading.

 

Figure 3
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  		Figure 3. Tumor-specific variation in the proportion of methylated genes in sporadic CRC (A and B), CRC cell lines (C), and FCCX (D). See legend for Fig. 2 for details.

 
Methylation patterns of individual genes. Only a fraction of the 24 TSGs were frequently methylated. Eleven genes in CRC [ESR1, CDH13, CHFR, RARB, APC, RASSF1(A), TIMP3, GSTP1, IGSF4, MLH1, and HIC1] and 6 genes in EC [RASSF1(A), CDH13, APC, GSTP1, CDKN2A, and TIMP3] were methylated in at least 15% of all CRC and EC tumors, accounting for 89% (424 of 475) and 82% (141 of 172) of all methylation events in these tumors, respectively (Table 2).

The most frequent genes methylated in both CRC and EC were CDH13 with methylation in 60% of CRC and 44% of EC, and APC in 34% of CRC and 38% of EC (Table 2). GSTP1 and TIMP3 were also commonly methylated in both cancers, as well as RASSF1(A), although it was methylated thrice more often in EC than CRC. Among genes showing significant (P < 0.05) tissue specificity, methylation of ESR1, CHFR, and RARB promoters was characteristic of CRC. Methylation of RASSF1(A) was typical of EC. These tissue-specific patterns persisted irrespective of MSI or MMR status or familial background of cancer.

The most sensitive genes to detect TSG methylator phenotype were ESR1, CDH13, and CHFR (values ranging 78–98%) in CRC and RASSF1(A), CDH13, and CDKN2A (range, 75–100%) in EC (Table 2). The most specific genes to TSG methylator phenotype were CHFR, RARB, and MLH1 in CRC (range, 74–76%) and CDKN2A, TIMP3, and GSTP1 (range, 78–87%) in EC.

GSTP1 (19 of 51 versus 3 of 49; P = 0.0002) and APC (25 of 51 versus 10 of 49; P = 0.003) were significantly more often methylated in familial (i.e., HNPCC-CRC and FCCX combined) than sporadic CRC tumors (Table 2). The FCCX group alone displayed methylated GSTP1 in 50% of tumors. ESR1, CDH13, CHFR, and MLH1 were instead significantly (P < 0.0001, 0.0001, 0.002, and 0.002, respectively) more often methylated in sporadic than familial CRC.

Quantitative levels of methylation. An advantage of MS-MLPA is that it allows quantification of methylation. The methylation dosage ratio for a given locus may range from 0 (0% of alleles methylated) to 1.0 (100% of alleles methylated) and 0.15 was our threshold value to consider a locus to be methylated. In clinical specimens, the average methylation dosage ratio over all methylated loci was 0.39 per tumor for both CRC and EC, considering the 11 and 6 most commonly methylated genes in CRC and EC, respectively (see above). Locus-specific average values ranged from 0.27 (GSTP1) to 0.46 (ESR1) in CRC and from 0.19 (CDKN2A) to 0.58[RASSF1(A)] in EC. In the cell lines with no contaminating normal cells, presumably monoallelic (0.5) and biallelic methylation (1.0) could be distinguished (Fig. 1). Corrected for tumor cell percentage (~60%; ref. 35), the average methylation ratio would be 0.65 (1/0.6 x 0.39) in our patient specimens, which could indicate monoallelic or biallelic methylation depending on the circumstances (e.g., homogeneity of tumor cell population).

MLH1 methylation and its relation to overall methylation status. Of all tumors with MLH1 methylation, 80% (20 of 25) displayed TSG methylator phenotype. The average overall number of methylated genes in these tumors was 8.6 versus 3.5 (P < 0.0001) for CRC and 3.8 versus 2.6 (nonsignificant) for EC in MLH1 methylation-positive and methylation-negative tumors, respectively. Dependence on MLH1 methylation was evident in all cohorts (Figs. 2 and 3). Tissue-specific methylation patterns persisted regardless of the MLH1 promoter methylation status, but percentages of tumors with methylation at a particular promoter were often higher when MLH1, too, was methylated (e.g., TIMP3 was methylated in 23% of CRC and 19% of EC tumors without MLH1 methylation and in 73% and 33%, respectively, with MLH1 methylation). Therefore, in addition to MMR status (in germ-line mutation-negative cases), MLH1 methylation is also a general predictor of tumor suppressor promoter methylation.

Promoter methylation in paired normal tissues. Paired samples of normal colon (n = 40), normal endometrium (n = 35), and blood (n = 13) were investigated for comparison, with a particular interest in groups with no known germ-line mutation. The presence of promoter methylation was significantly associated with tumors (Table 2) when compared with matching normal tissue (Table 3 ). Low-level methylation (with mean methylation dosage ratios ~0.2) was primarily found for GSTP1, ESR1, and CDKN2A; additionally, RASSF1(A) was methylated in some normal endometrial samples but not in normal colorectal mucosa (Table 3). Contrary to some literature reports [e.g., ESR1 (7)], no clear-cut correlation between normal tissue methylation and age was seen, or if present, the effect was limited to selected groups of patients. Blood (lymphoblastoid or lymphocyte) DNA was completely unmethylated with the exception of DAPK1, IGSF4, and GSTP1, which were each methylated once in separate specimens.


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  		Table 3. TSG methylation in paired normal tissues and blood

 

   Discussion
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 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
Disclosure of Potential...
 References
 
The CIMP phenotype was originally defined as methylation at three or more of seven "cancer-specific" loci [MINT ("methylated in tumors") 1, MINT31, p14 gene, p16 gene, THBS1, MLH1, and TIMP3], which had been identified through screening colon tumors and normal mucosa for differential methylation (7). Since then, a multitude of investigations addressing the occurrence and implications of CIMP in cancer has been published (34, 36, 37) but a uniform definition for CIMP is still lacking and the available information is mostly based on CRC, especially its sporadic form. Among the 24 TSGs we studied, some represented previously identified CIMP indicator genes [e.g., MLH1, TIMP3, CDKN2A encoding p14ARF, CDKN2B encoding p15INK4b, TP73, and APC; (7, 34, 36)], whereas others did not. Our observations of significant differences in DNA methylation profiles between CRC and EC emphasize that epigenetic mechanisms target different TSGs in different tumors, probably reflecting developmental mechanisms specific to tumor type, and that TSG methylator phenotype has to be defined separately for each type of cancer.

Studies on sporadic CRC have shown that tumors with versus without CIMP have different clinicopathologic features, including type of genomic instability, and that these features in CIMP-positive tumors are modified by methylation of MLH1 or the lack of it (38–40). In our investigation, MLH1 methylation had distinct roles depending on the germ-line mutation status. Whereas abnormal MMR in HNPCC mostly did not require MLH1 methylation (Fig. 2A and B), two CRC tumors from HNPCC patients with MLH1 germ-line mutation showed low-level MLH1 methylation (methylation dosage ratios of 0.18 in both), which was likely to serve as a "second hit" with the purpose to inactivate the wild-type allele (41); it was also an indicator of a more generalized methylator phenotype (Fig. 2A). In the remaining tumors, the presence of MLH1 methylation, on the average dosage level of 0.38 for FSSEC (Fig. 2C) and 0.42 for sporadic CRC (Fig. 3A), showed a tight correlation with MSI and IHC loss of MLH1 protein and served as an indicator of TSG methylator phenotype. The four CRC cell lines with MLH1 methylation displayed MLH1 methylation ratios close to 1.0 (compatible with biallelic methylation in the absence of contaminating normal cells) and the highest average numbers of methylated genes (Table 2; Fig. 3C), in agreement with previous observations of excessive CpG island hypermethylation in cancer cell lines compared with primary tumors (42). Finally, tumors without MLH1 methylation were MSS and consisted of groups with and without TSG methylator phenotype (Figs. 2D and 3B and D).

In contrast to other tumor categories, which showed fairly unimodal distributions, the FCCX group revealed a clear dichotomy in the overall methylation status in the absence of MLH1 promoter methylation (Fig. 3D). Tumors from this group tend to lack changes that are common in colorectal carcinogenesis, such as MSI, chromosomal instability, active (nuclear) β-catenin, and TP53 mutations (23). Analysis of subcategories with (n = 9) versus without (n = 9) TSG methylator phenotype showed that nonactive (membranous) β-catenin was more frequent in the methylator-positive group (75% versus 43%), combined with location in the proximal colon (57% versus 25%). Young and colleagues (43) recently reported frequent BRAF mutations combined with MINT31 CpG island hypermethylation in familial CRC not representing familial adenomatous polyposis or HNPCC and including MSS tumors. The authors suggested a serrated pathway of origin for these tumors. In our FCCX tumors with TSG methylator phenotype (MSS with one exception), BRAF mutations were infrequent and the tumors were not known to exhibit serrated features, so the extent of molecular similarity between the addressed entities remains to be settled by future studies.

By examining CRC or colorectal adenoma patients not belonging to adenomatous polyposis or HNPCC families, Frazier and colleagues (14) and Ricciardiello and colleagues (44) found that a generalized methylator phenotype and/or MLH1 promoter methylation in tumor tissue were associated with a positive family history of cancer, suggesting that promoter methylation may have a heritable genetic component. Samowitz and colleagues (38) observed no such association. Even more interesting, occasional patients with MSI tumors may have germ-line "epimutation" of MLH1 (15, 16, 45, 46) or MSH2 (17), where constitutional hypermethylation of one allele occurs in all or most tissues leading to silencing of expression from that allele, and this state may be present in successive generations. We found no support for a possible heritable basis for the methylation changes we observed in germ-line mutation-negative families (FCCX and FSSEC) because methylation profiles (presence versus absence of TSG methylator phenotype) were mostly discordant between different affected members from a given family (data not shown), and methylation was virtually absent in blood or adjacent normal tissue (Table 3). Incomplete concordance between family members does not, however, exclude the possibility of a genetic basis for methylation changes. Many genes involved in DNA methylation or chromatin modification are known to have functional low-penetrance variants (47), which may act as constitutional modifiers in hereditary disorders, such as HNPCC. Our preliminary data show that at least one such variant (C677T polymorphism in MTHFR) is significantly associated with the TSG methylator phenotype in the present series.7

Our study highlights the advantages of MS-MLPA over many alternative methods, especially as it has the possibility to detect and quantify methylation in a large set of genes and promoters simultaneously using only small amounts of template DNA, which can be paraffin derived. Findings obtained by the present approach may have important scientific and clinical implications. Genetic and epigenetic characterization of tumor tissues may provide clues for novel susceptibility genes in families with unknown predisposition [e.g., FCCX; this study and Sanchez-de-Abajo and colleagues (48)]. Quantification of MLH1 promoter methylation may distinguish HNPCC-CRC from sporadic microsatellite-unstable CRC [this study and Bettstetter and colleagues (49)]. Detection of epigenetic alterations at premalignant stages [e.g., in endometrial hyperplasia; Esteller and colleagues (50)] may facilitate cancer prevention in predisposed individuals. As indicated by these selected examples, knowledge of alterations that on different levels contribute to tumor development provides the basis for improved diagnostics, prevention, and therapy in the respective cancers.


   Disclosure of Potential Conflicts of Interest
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 Abstract
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 Materials and Methods
 Results
 Discussion
 Disclosure of Potential...
References
 
No potential conflicts of interest were disclosed.


   Acknowledgments
 
Grant support: Sigrid Juselius Foundation and Finnish Cancer Foundation (P. Peltomäki and S. Knuutila); Academy of Finland (P. Peltomäki and W.M. Abdel-Rahman); Biocentrum Helsinki (P. Peltomäki); Finnish Cultural Foundation, Helsinki Graduate School in Biotechnology and Molecular Biology, and Maud Kuistila Memorial Foundation (M. Ollikainen); and Graduate School in Computational Biology, Bioinformatics, and Biometry as well as Academy of Finland, the Systems Biology and Bioinformatics Program (SYSBIO; S. Ruosaari).

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.

We thank the patients and our clinical collaborators for samples and Saila Saarinen, Annette Gylling, and Taina Nieminen for assistance in laboratory assays.


   Footnotes
 
Note: Supplementary data for this article are available at Cancer Research Online (http://cancerres.aacrjournals.org/).

5 http://www.mrc-holland.com Back

6 W.M. Abdel-Rahman et al., unpublished data. Back

7 E.I. Joensuu et al., unpublished data. Back

Received 12/13/07. Revised 4/10/08. Accepted 4/22/08.


   References
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 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Disclosure of Potential...
 References
 

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T. T. Nieminen, A. Gylling, W. M. Abdel-Rahman, K. Nuorva, M. Aarnio, L. Renkonen-Sinisalo, H. J. Jarvinen, J.-P. Mecklin, R. Butzow, and P. Peltomaki
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