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Abstract

  1. Top of page
  2. Abstract
  3. Previously Reported Methods/Reports on CIMP
  4. Proposal of CIMP+ CRC
  5. Hierarchical Clustering Using Quantitative Data to Detect CIMP+ CRC
  6. Lack of Group-2 Markers in CIMP+ Model: Importance of Comprehensive Search for Candidate Markers
  7. Absence of CIMP? Importance of Quantitative Analysis and Classifier Marker Selection
  8. Proposal of CIMP-Low
  9. Classification into Three Subsets
  10. Our CRC Epigenotyping
  11. Conclusion
  12. Acknowledgments
  13. References

A subgroup of colorectal cancer (CRC) shows non-random accumulation of aberrant DNA methylation, so-called CpG island methylator phenotype (CIMP), which was associated with microsatellite instability and BRAF mutation. As just one group of methylation markers was suitable to extract CIMP+/CIMP-high, and had been commonly used in the “one-panel method”, it had been unclear whether another cluster of CRC with DNA methylation accumulation exists in microsatellite-stable CRC. We therefore epigenotyped CRC by a comprehensive approach, that is, the two-way unsupervised hierarchical clustering method using highly quantitative methylation data by a single detection method, MALDI-TOF mass spectrometry, on novel regions selected genome-widely through methylated DNA immunoprecipitation on array analysis. CRC was clearly clustered into three DNA methylation epigenotypes, high-, intermediate- and low-methylation epigenotypes (HME, IME, and LME, respectively). Methylation markers are clustered into two distinct groups: Group-1 methylated specifically in HME and including most reported CIMP-related markers; and Group-2 methylated both in HME and IME. While suitable markers to detect a subgroup of CRC with intermediate methylation and correlation to KRAS mutation have been expected to be developed, our data indicated that a “two-panel method” is necessary to properly classify CRC into three epigenotypes, the first panel to extract HME using Group-1 markers, and the second panel to divide the remaining into IME and LME using Group-2 markers. Here we review and compare our recent study and reported CRC classification methods by DNA methylation information, and propose the use of two panels of methylation markers as CRC classifiers. (Cancer Sci 2011; 102: 18–24)

Abbreviations
CIMP

CpG island methylator phenotype

CRC

colorectal cancer

HME

high-methylation epigenotype

IME

intermediate-methylation epigenotype

LME

low-methylation epigenotype

MCA

methylated CpG island amplification

MeDIP

methylated DNA immunoprecipitation

MINT

methylated-in-tumor

MSI

microsatellite instability

MSP

methylation-specific PCR

Epigenetic information is modification of DNA and its associated proteins, not the DNA sequence itself, and is heritable in cell division. It is widely accepted now that cancer arises through accumulation of genetic alterations as well as epigenetic alterations, such as aberrant DNA methylation to silence gene expressions, and loss of imprinting to double expression of imprinted genes.(1–3) The importance of epigenetic alterations is noted not only in cancer progression, but also in cancer initiation,(3,4) as the alterations can be accumulated in the pre-cancerous “normal” tissues to modify a cancer risk,(5,6) and the risk might be managed by target therapy.(7)

Gene silencing by DNA methylation of its promoter region is one of the most important epigenetic mechanisms to inactivate gene expression.(2) Genome-wide search of genes using aberrant methylation as markers is useful to identify novel tumor-suppressor genes and methylation markers for cancer classification.(8–13) Several approaches to detect methylated regions have been developed, originally analyzing limited regions represented by methylation-sensitive restriction enzymes,(14) and recently analyzing regions on a genome-wide scale.(15–19)

It has been reported that a subset of cancer cases shows aberrant methylation in many genes/loci and another shows methylation in less number or none of the genes/loci at all (Table 1, Fig. 1).(12,20–23) These non-random accumulations of methylation were first indicated in CRC in 1999, proposing “CpG island methylator phenotype” as a phenotype of cancer cases with aberrant methylation of significantly more numbers of genomic marker regions.(12) Most studies during the last decade have used one group of classifier markers, including the original CIMP markers (namely, the “one-panel method”) (Fig. 1A,B). We recently revealed through unsupervised two-way hierarchical clustering that CRC is clearly classified into three groups by DNA methylation information only: HME, IME, and LME (Fig. 1D).(23) Intermediate-methylation epigenotype strongly correlates to KRAS-mutation(+) CRC. It is noteworthy that methylation markers are clustered into two distinct groups, Group-1 and Group-2 (Fig. 1D). Group-1 markers are methylated specifically in HME, so are suitable to extract HME CRC. Group-2 markers are methylated both in HME and IME, so can divide CRC into IME and LME after exclusion of HME CRC. Here we review and compare our epigenotyping model and reported CRC classification methods, and propose a “two-panel method” to classify CRC properly (Fig. 1D).

Table 1.   Reports on colorectal cancer (CRC) classification by methylation information
Toyota et al.(12)Yamashita et al.(24)Weisenberger et al.(20)Ogino et al.(21)Shen et al.(22)Yagi et al.(23)
  1. CIMP, CpG island methylator phenotype; COBRA, combined bisulfite restriction analysis; HME, high-methylation epigenotype; IME, intermediate-methylation epigenotype; LME, low-methylation epigenotype; MCA, methylated CpG island amplification; MeDIP, methylated DNA immunoprecipitation; MS-AFLP, methylation-sensitive amplified fragment length polymorphism; MSP, methylation-specific PCR; NA, not applicable; RDA, representation difference analysis.

Year
 199920032005200620072010
Marker selection (sample used)
 MCA-RDA (Caco2)MS-AFLP (32 CRCs)MethyLight markersReported markersReported markersMeDIP-chip & expression array (HCT116, SW480)
No. of original markers, +no. of previously reported markers
 33[RIGHTWARDS ARROW]7, +0203[RIGHTWARDS ARROW]30, +6195[RIGHTWARDS ARROW]88, +0 0, +80, +271311[RIGHTWARDS ARROW]44, +16
Quantitative methylation analysis method
 COBRAMS-AFLP MSPMethyLightMethyLightPyrosequence COBRA MCA MSPMassARRAY
Classification method
 Methylation frequencyMethylation frequencyHierarchical clusteringMethylation frequencyHierarchical clusteringHierarchical clustering
Methylation phenotypes
 CIMP+  CIMP−(Absent)CIMP+ CIMP−CIMP-high CIMP-low CIMP-0CIMP1 CIMP2 CIMP-negativeHME IME LME
No. of phenotypes
 202333
Marker panel
 MethylationNAMethylationMethylationGenetic and methylationMethylation
No. of methylation marker panels
 1NA11NA2
See also
 Fig. 1ANAFig. 1AFig. 1BFig. 1CFig. 1D
image

Figure 1.  Models for phenotypes of methylation accumulation. X-axes, colorectal cancer (CRC) cases; Y-axes, markers/genes. Grey boxes indicate methylation(+). (A) CpG island methylator phenotype (CIMP)+/−.(12,20) The representative marker panel contains five markers. CIMP+, colorectal cancer (CRC) methylated in 3–5 among five markers, which correlates to microsatellite instability (MSI)-high and BRAF-mutation(+); CIMP−, CRC methylated in 0–2 among five markers. MSS, microsatellite stable. (B) CIMP-high/-low/-0.(21,28) Similar to the CIMP+/− model, only one marker panel is used, and the representative marker panel contains eight markers. CIMP-0, CRC with no methylation; CIMP-high, CRC methylated in 6–8 among eight markers; CIMP-low, CRC methylated in 1–5 among eight markers. CIMP-low was reported to correlate possibly with KRAS mutation(+). (C) CIMP1/2/-negative.(22) Genetic markers are also used in determining CIMP status, but they perform better than methylation markers in classification. CIMP1, cluster with BRAF mutation and CIMP1 marker methylation; CIMP2, cluster with KRAS mutation and CIMP2 marker methylation; CIMP-negative, cluster with p53 mutation and absence of methylation. (D) High-methylation epigenotype (HME), intermediate-methylation epigenotype (IME), and low-methylation epigenotype (LME).(23) HME, CRC with methylation of Group-1 and Group-2 markers, correlating strongly to MSI-high and BRAF-mutation(+). In MSS CRC, there is no clear subset showing random methylation of Group-1 markers like the CIMP-high/-low/-0 model. Instead, there is another clear subset IME showing accumulation of methylation of Group-2 markers only, and correlating to KRAS-mutation(+). Two-step classification using two marker panels is proposed: the first panel to extract CRC with Group-1 marker methylation as HME; and the second panel to divide the remaining into CRC with Group-2 marker methylation as IME and the others as LME. There is no need to use genetic markers in this classification if using our novel Group-2 methylation markers.

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Proposal of CIMP+ CRC

  1. Top of page
  2. Abstract
  3. Previously Reported Methods/Reports on CIMP
  4. Proposal of CIMP+ CRC
  5. Hierarchical Clustering Using Quantitative Data to Detect CIMP+ CRC
  6. Lack of Group-2 Markers in CIMP+ Model: Importance of Comprehensive Search for Candidate Markers
  7. Absence of CIMP? Importance of Quantitative Analysis and Classifier Marker Selection
  8. Proposal of CIMP-Low
  9. Classification into Three Subsets
  10. Our CRC Epigenotyping
  11. Conclusion
  12. Acknowledgments
  13. References

In 1999, Toyota et al. developed MCA to represent methylated genomic regions using methylation-sensitive restriction enzymes. Thirty-three genomic DNA clones that aberrantly methylated in cancer cell line Caco2, but not in normal colon tissue, were identified using a subtraction method, representation difference analysis.(10) The 33 clones were named MINT. Most of the MINT clones showed methylation not only in CRC, but also in normal colon mucosa in an age-related manner, thus were called type A. These type A clones were methylated in most CRC cases, so are considered to be non-classifier markers. The remaining seven clones were methylated specifically in cancer, not in normal mucosa, thus called type C. The type C markers were methylated in CRC less frequently than type A, and classified CRC cases sharply into two groups: a group with methylation in three or more loci; and a group with extremely rare methylation. The former CRC subset was considered as CIMP+, and these type C MINT clones were considered as CIMP markers (Table 1, Fig. 1A).(12)

Hierarchical Clustering Using Quantitative Data to Detect CIMP+ CRC

  1. Top of page
  2. Abstract
  3. Previously Reported Methods/Reports on CIMP
  4. Proposal of CIMP+ CRC
  5. Hierarchical Clustering Using Quantitative Data to Detect CIMP+ CRC
  6. Lack of Group-2 Markers in CIMP+ Model: Importance of Comprehensive Search for Candidate Markers
  7. Absence of CIMP? Importance of Quantitative Analysis and Classifier Marker Selection
  8. Proposal of CIMP-Low
  9. Classification into Three Subsets
  10. Our CRC Epigenotyping
  11. Conclusion
  12. Acknowledgments
  13. References

In 2006, Weisenberger et al.(20) used quantitative methylation data to classify CRC using a powerful classification method, unsupervised hierarchical clustering, and successfully confirmed the existence of CIMP. They carried out a first screen of all the 195 MethyLight markers available at that time against 10 pairs of normal colon and tumor tissue samples to select 92 cancer-specific methylation markers. Second, the quantitative methylation status of the 92 markers in 48 pairs of normal colon and tumor tissue samples was analyzed by MethyLight. Hierarchical clustering using these data revealed that there is a cluster of CRC showing high methylation and strong correlation to BRAF mutation and MSI. They unfortunately did not find another cluster of CRC showing intermediate methylation at this second step. Then a third independent set of 187 tumors were analyzed, and a new, more suitable panel of five methylation markers to determine CIMP+ was proposed, comprising CACNA1G, IGF2, NEUROG1, RUNX3, and SOCS1 (Table 1, Fig. 1A). CACNA1G possesses MINT31, one of the original CIMP markers by Toyota et al.(12), at 2 kb upstream of its transcription start site.(23)

Lack of Group-2 Markers in CIMP+ Model: Importance of Comprehensive Search for Candidate Markers

  1. Top of page
  2. Abstract
  3. Previously Reported Methods/Reports on CIMP
  4. Proposal of CIMP+ CRC
  5. Hierarchical Clustering Using Quantitative Data to Detect CIMP+ CRC
  6. Lack of Group-2 Markers in CIMP+ Model: Importance of Comprehensive Search for Candidate Markers
  7. Absence of CIMP? Importance of Quantitative Analysis and Classifier Marker Selection
  8. Proposal of CIMP-Low
  9. Classification into Three Subsets
  10. Our CRC Epigenotyping
  11. Conclusion
  12. Acknowledgments
  13. References

MINT clones identified by MCA were considered to belong to Group-1 (Fig. 2A), so were actually suitable to extract CIMP+/HME CRC. But unfortunately MINT clones did not include Group-2 markers, so could not detect IME.(23) If more than one CRC cell line (Caco2) had been analyzed by MCA, or a more genome-wide approach had been available in the analysis of Caco2, Group-2 markers might have been identified. Although p16CDKN2A and hMLH1 were often analyzed with MINT clones, hMLH1 is a Group-1 marker showing no methylation in IME or LME (Fig. 2A). p16CDKN2A shows only slightly higher methylation in IME than LME, so still belongs to Group-1.(23)

image

Figure 2.  Classification of methylation markers. (A) LOX or many CpG island methylator phenotype (CIMP) markers (e.g. methylated-in-tumor [MINT]1 and MINT2) show methylation specifically to high-methylation epigenotype (HME; H) only, and belong to Group-1 (H >> I = L). Other CIMP markers (e.g. CACNA1G and MINT17) show slightly higher methylation in intermediate-methylation epigenotype (IME; I), but hardly distinguish IME and low-methylation epigenotype (LME; L) because of the tiny difference (H >> I > L). Group-2 markers show significantly higher methylation in IME than LME, thus can distinguish the two epigenotypes. Some Group-2 markers (e.g. HAND1 and ELMO1) show even higher methylation in HME (H > I > L), and some (e.g. THBD and ADAMTS1) show similar, very high methylation levels in both HME and IME (H = I > L). Among reported CIMP markers, only NEUROG1 belongs to Group-2. There are non-classifier genes (e.g. CDO1, CIDEB, and RASSF1A) (H = I = L). (B) If a marker shows a high methylation level specifically to IME or LME only, it would not be necessary to use two panels at two steps (Fig. 1D) and classification would be much easier. These specific markers were not identified, however, at least by our previous studies. There were reports suggesting that RASSF2 or IGFBP3 might be specific markers for intermediate methylation phenotype,(29,35) but these genes were shown to belong to the H = I > L pattern (Fig. 3A) in our study.

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NEUROG1 is a Group-2 marker, but shows even higher average methylation levels in HME than IME (See Fig. 3A, H > I > L), so was still suitable to be selected in the marker panel for CIMP+. The other four Weisenberger markers are methylated specifically in HME, and show low and very similar methylation levels in IME and LME (Fig. 3A). Overall, Weisenberger’s panel is very suitable to detect CIMP+/HME, but cannot identify IME. Two possibilities can be raised why the IME cluster was not identified in their study. First, the 48 tumor samples in the second screen might not have been enough to make IME cluster clearly, although as many as 19 KRAS-mutation(+) CRC were included in the 48. Second, their 195 MethyLight markers(20) might not have included enough Group-2 markers to make IME cluster. In fact, the 26 Group-2 markers we identified(23) were not included in the 195 MethyLight markers other than NEUROG1. A comprehensive genome-wide search for marker candidates is suggested to be important and necessary.

image

Figure 3.  Quantitativity of MALDI-TOF mass spec-trometry (MassARRAY). (A) MassARRAY is highly quantitative and reproducible. Duplicated methylation control samples (methylation 0%, 25%, 50%, 75%, 100%) showed a linear standard curve with high correlation coefficient (R2). (B) Because of the sequence difference between methylated and unmethylated DNA after bisulfite treatment, their amplification efficiencies could be different and PCR bias is often observed. Methylated alleles would tend to be more efficiently amplified, as shown. When R2 was low (≤0.9), the primer pair was excluded or redesigned.

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Absence of CIMP? Importance of Quantitative Analysis and Classifier Marker Selection

  1. Top of page
  2. Abstract
  3. Previously Reported Methods/Reports on CIMP
  4. Proposal of CIMP+ CRC
  5. Hierarchical Clustering Using Quantitative Data to Detect CIMP+ CRC
  6. Lack of Group-2 Markers in CIMP+ Model: Importance of Comprehensive Search for Candidate Markers
  7. Absence of CIMP? Importance of Quantitative Analysis and Classifier Marker Selection
  8. Proposal of CIMP-Low
  9. Classification into Three Subsets
  10. Our CRC Epigenotyping
  11. Conclusion
  12. Acknowledgments
  13. References

When methylation profiles of hMLH1, MGMT, p16CDKN2A, p14ARF, APC, and CDH1 in 207 CRC were analyzed by Yamashita et al.(24) using MSP, the number of methylated loci per tumor showed a non-bimodal distribution. The result denied non-random accumulation of methylation in a subgroup of CRC, and suggested the absence of CIMP (Table 1). The concept and definition of CIMP had been arbitrary at that time, as they pointed out, and they successfully made a stir in the argument on CIMP. However, MSP is not a quantitative analysis and could give false positive data by detecting very infrequent methylation at few CpG sites. In fact, MGMT seemed to be the most frequently methylated gene in their MSP analysis, which caused 24 (12%) additional CRC cases with one methylated locus, that is, a decrease of 24 CRC cases without methylation.(24) But our quantitative methylation data indicated that MGMT is an outlier, non-classifier gene belonging to neither Group-1 nor Group-2 due to its low methylation score in any epigenotypes of CRC.(23)

In Yamashita’s(25) report, 203 methylated regions were also identified by methylation-sensitive amplified fragment length polymorphism analysis of 32 CRCs, and methylation of 30 chosen markers did not show a non-random pattern but distributed evenly in CRC cases again.(24) This suggested to us that a panel of randomly chosen markers could give no cluster of CRC cases due to contamination with many non-classifier markers. In Weisenberger’s classification, non-cancer-specific MethyLight markers were excluded before hierarchical clustering analysis, and most cancer-specific markers were further excluded in developing the best CIMP panel.(20) Two-way hierarchical clustering in our study revealed the existence of two major marker groups, Group-1 and Group-2, but also the existence of outlier, non-classifier genes.(23) Methylation epigenotype, or CIMP, is not a phenotype of simultaneous methylation of all the CpG islands in a genome. We must develop a decision panel by selecting classifier genes cautiously.

Proposal of CIMP-Low

  1. Top of page
  2. Abstract
  3. Previously Reported Methods/Reports on CIMP
  4. Proposal of CIMP+ CRC
  5. Hierarchical Clustering Using Quantitative Data to Detect CIMP+ CRC
  6. Lack of Group-2 Markers in CIMP+ Model: Importance of Comprehensive Search for Candidate Markers
  7. Absence of CIMP? Importance of Quantitative Analysis and Classifier Marker Selection
  8. Proposal of CIMP-Low
  9. Classification into Three Subsets
  10. Our CRC Epigenotyping
  11. Conclusion
  12. Acknowledgments
  13. References

An additional subset, such as CIMP-intermediate or CIMP-low, has been described to embrace tumors with intermediate levels of methylation.(26,27) In 2006, for example, Ogino et al.(21) proposed a CIMP-low subset of CRC, showing 1–3 methylated promoters among CACNA1G, p16CDKN2A, CRABP1, hMLH1, and NEUROG1. They reported that the CIMP-low CRC is associated with male sex and KRAS mutations, and thus suggested that CIMP-low CRC is a different subtype from CIMP-high and CIMP-0. This classification is not ideal, but might work as NEUROG1 is a Group-2 marker showing higher methylation in IME than LME (Fig. 2). Colorectal cancer with methylation of NEUROG1 is regarded as CIMP-low, although CRC with random methylation of other genes is also regarded as CIMP-low. In another report, they suggested using eight markers (CACNA1G, p16CDKN2A, CRABP1, IGF2, hMLH1, NEUROG1, RUNX3, and SOCS1) and defining CRC with 1/8–5/8 methylated promoters as CIMP-low, 0/8 as CIMP-0, and 6/8–8/8 as CIMP-high (Fig. 1B).(28,29)

Ogino et al.(30) noted, however, that a difference between CIMP-low and CIMP-0 is not clear-cut as these methylation markers were specific for CIMP-high and not ideal for identification of CIMP-low, and that sensitive and specific markers for CIMP-low need to be determined if CIMP-low really exist. This is a good support for our two-panel method. They reported that BRAF-mutation(+) CRC showed a non-random pattern of CpG island methylation, whereas KRAS-mutation(+) CRC showed a random pattern, by analyzing 16 regions.(31) This also indicated that these previous markers specific for HME/CIMP-high, BRAF-mutation(+) CRC could show methylation in IME/CIMP-low, KRAS-mutation(+) CRC only randomly. If Group-2 markers showing a non-random pattern of methylation in KRAS-mutation(+) CRC are used in a panel, the difference between IME/CIMP-low and LME/CIMP-0 will be clear-cut.

Classification into Three Subsets

  1. Top of page
  2. Abstract
  3. Previously Reported Methods/Reports on CIMP
  4. Proposal of CIMP+ CRC
  5. Hierarchical Clustering Using Quantitative Data to Detect CIMP+ CRC
  6. Lack of Group-2 Markers in CIMP+ Model: Importance of Comprehensive Search for Candidate Markers
  7. Absence of CIMP? Importance of Quantitative Analysis and Classifier Marker Selection
  8. Proposal of CIMP-Low
  9. Classification into Three Subsets
  10. Our CRC Epigenotyping
  11. Conclusion
  12. Acknowledgments
  13. References

In 2007, Shen et al.(22) proposed through genetic and epigenetic analysis that colon cancer was classified into three subsets, CIMP1, CIMP2, and CIMP-negative (Table 1, Fig. 1C). This report successfully showed the existence of three clusters of CRC with different molecular characteristics: one with MSI-high, BRAF-mutation(+) and methylation, another with KRAS-mutation(+) and different methylation, and the other with p53 mutation and an absence of these methylation.

Genetic markers performed equally well or better than epigenetic markers in their report, so they highlighted the importance of integrated genetic and epigenetic analysis.(22)KRAS mutation itself was used in the CIMP2 marker panel, for example. The questions whether CRC is classified into three subsets by methylation accumulation phenotypes only, and whether there are methylation markers suitable to detect intermediate methylation subgroup or KRAS-mutation(+) CRC, were therefore not clearly answered at this stage.

The authors analyzed 27 previously reported regions using four different methylation detection methods: 13 regions by Pyrosequencing; 7 by COBRA; 6 by MCA; and 1 by MSP.(22) They found methylation of NEUROG1 to be highly specific to CIMP2, so their hierarchical clustering might be quite similar to our classification. They also reported methylation of several MINT loci to be highly specific to CIMP2 and to predict CIMP2 better than NEUROG1, by analyzing methylation using a competitive PCR method MCA. The MINT loci, however, should show no or very small differences in average methylation levels between IME and LME and belong to Group-1 markers (Fig. 2), so were considered to be difficult to classify CIMP2 and CIMP-negative.(23) In any classification study, all the methylation data are to be completed using a quantitative method.(32)

Our CRC Epigenotyping

  1. Top of page
  2. Abstract
  3. Previously Reported Methods/Reports on CIMP
  4. Proposal of CIMP+ CRC
  5. Hierarchical Clustering Using Quantitative Data to Detect CIMP+ CRC
  6. Lack of Group-2 Markers in CIMP+ Model: Importance of Comprehensive Search for Candidate Markers
  7. Absence of CIMP? Importance of Quantitative Analysis and Classifier Marker Selection
  8. Proposal of CIMP-Low
  9. Classification into Three Subsets
  10. Our CRC Epigenotyping
  11. Conclusion
  12. Acknowledgments
  13. References

Attention in our methods.

We therefore carried out epigenotyping of CRC very carefully by comprehensive approach, i.e., two-way unsupervised hierarchical clustering using highly quantitative methylation data by a single detection method, MALDI-TOF mass spectrometry (MassARRAY; Sequenom, San Diego, CA, USA),(33) using genome-widely selected novel regions through MeDIP-chip analysis.(23)

Although MeDIP is known to be innaccurate for analyzing low-CpG regions, it is a powerful tool to identify methylated high-CpG regions, for example, promoter CpG islands.(16,34) We used MeDIP on two CRC cell lines, MSI-high HCT116 and microsatellite-stable SW480. The MeDIPed samples underwent unbiased amplification by in vitro transcription before hybridization, and samples were hybridized to Human Promoter 1.0R tiling array covering 4 071 296 CpG sites around over 25 500 promoter regions comprehensively.(16,23)

To select genes whose promoter methylation causes gene silencing, we also carried out expression array analysis of the CRC cell lines with/without treatment by 5-aza-2′-deoxycytidine and trichostatin A, and selected 55 genes showing expression in normal colon, silencing in methylated cell lines, and re-expression after 5-aza-2′-deoxycytidine and trichostatin A treatment, from 1311 candidates.(23)

To obtain highly quantitative data for these 55 genes and previously reported 19 regions, quantitativity of 74 primer pairs for MassARRAY was carefully validated using methylation control samples (Fig. 3).(23) Because of the sequence difference between methylated DNA and unmethylated DNA after bisulfite treatment, amplification efficiencies of the two could be different and PCR bias is often observed. A linear standard curve was drawn and the correlation coefficient (R2) was calculated at each CpG unit. When there was no PCR bias, methylated and unmethylated alleles were amplified equally, and R2 would be high (>0.9) (Fig. 3A). When there was PCR bias, R2 would be low (≤0.9), usually because methylated alleles were amplified more efficiently than unmethylated alleles (Fig. 3B). Only when three or more CpG units with R2 > 0.9 existed, the primer pairs were considered to be highly quantitative enough and used for further analyses. Primers for 60 markers including 44 novel markers and 16 reported genes/loci were successfully developed.

Clinical CRC samples were microscopically examined for determination of cancer cell contents, and were dissected to enrich cancer cells to 40% or more when necessary.(23)

Three epigenotypes of CRC cases and two clusters of markers.

Two-way unsupervised hierarchical clustering classified CRC cases into three distinct epigenotypes: HME, IME, and LME (Fig. 1D). The high-methylation epigenotype strongly correlates to BRAF mutation and MSI-high, and IME strongly correlates to KRAS mutation.(23) Without genetic markers, CRC is clearly classified into three subclasses using methylation information only. It is also noteworthy that IME KRAS-mutation(+) CRC showed significantly worse prognoses.

Genes were also clustered into two major groups, Group-1 and Group-2, forming several outlier/non-classifier genes as mentioned above (Figs 1D, 2A).(23) Markers methylated specifically in IME or LME have not been identified (Fig. 2B). Two marker panels are therefore necessary to classify CRC at two steps: the first panel to extract HME using Group-1 markers; and the second panel to divide the remaining into IME and LME (Fig. 1D). If we answer to Ogino’s question,(30) Group-2 markers could be the suitable markers for the intermediate methylation phenotype, although combined use of Group-1 and Group-2 markers are necessary. Previous CIMP-related markers were all categorized into Group-1 markers except NEUROG1. Genome-wide search for novel markers enabled us to avoid bias of available markers to Group-1 in the previous studies.

Nagasaka et al.(35) analyzed methylation of seven canonical CIMP markers and seven new markers in CRC, and reported that methylation frequency of seven canonical CIMP markers was high in BRAF-mutation(+) CRC but low in KRAS-mutation(+) CRC, whereas methylation frequency of the additional markers was high in both BRAF-mutation(+) and KRAS-mutation(+) CRC. Their argument could be similar to ours.

Why do oncogene mutations correlate to epigenotypes?

The strong correlations between HME and BRAF(+), and between IME and KRAS(+), are interesting, and possibly suggest a causal link between methylation epigenotypes and oncogene mutation.(23,35) Oncogene activation might somehow induce different epigenetic, genome-wide alterations (Fig. 4A). In fact, silencing of genes occurred in Kras-transformed NIH3T3 but not in untransformed NIH3T3, and essential effectors for the epigenetic gene silencing in Kras-transformed NIH3T3 were reported.(36) Another possibility is that promoter methylation might be accumulated in an early step of tumorigenesis.(3) Oncogene activation is known to induce a premature form of cellular senescence and fall into irreversible arrest to block cellular proliferation.(37) While cells without methylation might senesce, cells with Group-1 and/or Group2 gene silencing might escape from oncogene-induced senescence and become tumor when an oncogene(s) is activated (Fig. 4B), as disruption of p16 and/or p53 leads to escape from oncogene-induced senescence.(38) For example, IGFBP3, reported to be induced in replicatively senescent HUVEC,(39) showed a high methylation rate in IME and HME CRC (Fig. 2A), although colon epithelium cells are different from endothelial cells. Further studies are necessary to establish which gene/signal activation is essential in oncogene-induced senescence, and which is actually inactivated by promoter methylation in tumor with a specific methylation epigenotype.

image

Figure 4.  Models of mechanisms correlating between oncogene mutation and methylation profile. M in a circle means methylation. (A) During the tumorigenesis step, oncogene activation might somehow induce specific methylation epigenotypes. (B) In an early step of tumorigenesis, promoter methylation might be accumulated and be requisite to escape from oncogene-induced senescence. Without methylation, BRAF or KRAS mutation might lead to cellular senescence, and other aberrations might be necessary to develop tumor. With Group-2 methylation accumulated, cells might escape from activated KRAS-induced senescence and could lead to tumor development, although Group-2 methylation might not be enough for cells to escape from activated BRAF-induced senescence. With Group-1 and Group-2 methylation, cells might escape from activated BRAF-induced senescence and could lead to tumor development. In this model, accumulated methylation of Group-1 and Group-2 genes could be a risk for colorectal cancer (CRC) with oncogene activation. HME, high-methylation epigenotype; IME, intermediate-methylation epigenotype; LME, low-methylation epigenotype.

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Conclusion

  1. Top of page
  2. Abstract
  3. Previously Reported Methods/Reports on CIMP
  4. Proposal of CIMP+ CRC
  5. Hierarchical Clustering Using Quantitative Data to Detect CIMP+ CRC
  6. Lack of Group-2 Markers in CIMP+ Model: Importance of Comprehensive Search for Candidate Markers
  7. Absence of CIMP? Importance of Quantitative Analysis and Classifier Marker Selection
  8. Proposal of CIMP-Low
  9. Classification into Three Subsets
  10. Our CRC Epigenotyping
  11. Conclusion
  12. Acknowledgments
  13. References

Comprehensive analysis through the selection of novel markers on a genome-wide scale and highly quantitative data allowed us to classify CRC, using methylation information only, into three epigenotypes: HME, IME, and LME. Methylation markers are classified into two clusters: Group-1 showing methylation in HME; and Group-2 showing methylation in HME and IME. These two groups of markers are proposed to be used at two steps in classifying CRC properly.

References

  1. Top of page
  2. Abstract
  3. Previously Reported Methods/Reports on CIMP
  4. Proposal of CIMP+ CRC
  5. Hierarchical Clustering Using Quantitative Data to Detect CIMP+ CRC
  6. Lack of Group-2 Markers in CIMP+ Model: Importance of Comprehensive Search for Candidate Markers
  7. Absence of CIMP? Importance of Quantitative Analysis and Classifier Marker Selection
  8. Proposal of CIMP-Low
  9. Classification into Three Subsets
  10. Our CRC Epigenotyping
  11. Conclusion
  12. Acknowledgments
  13. References