Comparing the DNA Hypermethylome
`with Gene Mutations
`in Human Colorectal Cancer
`Kornel E. Schuebel1[*, Wei Chen1,2[
`, Leslie Cope3[
`, Sabine C. Glo¨ ckner4[
`, Hiromu Suzuki5, Joo-Mi Yi1, Timothy A. Chan1,
`Leander Van Neste6, Wim Van Criekinge7, Sandra van den Bosch8, Manon van Engeland8, Angela H. Ting1, Kamwing Jair9,
`Wayne Yu1, Minoru Toyota5, Kohzoh Imai5, Nita Ahuja4, James G. Herman1, Stephen B. Baylin1,2*
`
`1 Cancer Biology Division, The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, Maryland, United States of America, 2 Predoctoral Training
`Program in Human Genetics, The Johns Hopkins University, Baltimore, Maryland, United States of America, 3 Biometry and Clinical Trials Division, The Sidney Kimmel
`Comprehensive Cancer Center at Johns Hopkins, Baltimore, Maryland, United States of America, 4 Department of Surgery, The Johns Hopkins University School of Medicine,
`Baltimore, Maryland, United States of America, 5 First Department of Internal Medicine, Sapporo Medical University, Sapporo, Japan, 6 Department of Molecular
`Biotechnology, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium, 7 Oncomethylome Sciences, Liege, Belgium, 8 Department of Pathology, University of
`Maastricht, Maastricht, The Netherlands, 9 Bionumerik Pharmaceuticals Inc., San Antonio, Texas, United States of America
`
`We have developed a transcriptome-wide approach to identify genes affected by promoter CpG island DNA
`hypermethylation and transcriptional silencing in colorectal cancer. By screening cell lines and validating tumor-
`specific hypermethylation in a panel of primary human colorectal cancer samples, we estimate that nearly 5% or more
`of all known genes may be promoter methylated in an individual tumor. When directly compared to gene mutations,
`we find larger numbers of genes hypermethylated in individual tumors, and a higher frequency of hypermethylation
`within individual genes harboring either genetic or epigenetic changes. Thus, to enumerate the full spectrum of
`alterations in the human cancer genome, and to facilitate the most efficacious grouping of tumors to identify cancer
`biomarkers and tailor therapeutic approaches, both genetic and epigenetic screens should be undertaken.
`
`Citation: Schuebel KE, Chen W, Cope L, Glo¨ ckner SC, Suzuki H, et al. (2007) Comparing the DNA hypermethylome with gene mutations in human colorectal cancer.
`PLoS Genet 3(9): e157. doi:10.1371/journal.pgen.0030157
`
`Introduction
`
`It is now well established that loss of proper gene function
`in human cancer can occur through both genetic and
`epigenetic mechanisms [1,2]. The number of genes mutated
`in human tumor samples is being clarified. Recently, Sjo¨ blom
`et al. [3] sequenced 13,023 genes in colorectal cancer (CRC)
`and breast cancer, and estimated an average of 14 significant
`mutations per tumor, suggesting that a relatively small
`number of genetic events may be sufficient to drive tumori-
`genesis. In contrast, the full spectrum of epigenetic alter-
`ations is not well delineated. The best-defined epigenetic
`alteration of cancer genes involves DNA hypermethylation of
`clustered CpG dinucleotides, or CpG islands, in promoter
`regions associated with the transcriptional inactivation of the
`affected genes [2]. These promoters are located proximal to
`nearly half of all genes [4] and are thought to remain
`primarily methylation free in normal somatic tissues. The
`exact number of such epigenetic lesions in any given tumor is
`not precisely known, although a growing number of screening
`approaches, none covering the whole genome efficiently, are
`identifying an increasing number of candidate genes [5–13].
`Given the large number of potential target promoters present
`in the genome, we hypothesized that many more hyper-
`methylated genes await discovery.
`Herein, we describe a whole human transcriptome micro-
`array screen to identify genes silenced by promoter hyper-
`methylation in human CRC. The approach readily identifies
`candidate cancer genes in single tumors with a high efficiency
`of validation. By comparing the list of candidate hyper-
`
`methylated genes with mutated genes recently identified in
`CRC [3], we establish key relationships between the altered
`tumor genome and the gene hypermethylome. Our studies
`provide a platform to understand how epigenetic and genetic
`alterations drive human tumorigenesis.
`
`Results
`
`Developing the Whole Transcriptome Approach
`Our first step towards a global identification of hyper-
`methylation-dependent gene expression changes was made by
`comparing, in a genome-wide expression array-based ap-
`proach, wild-type HCT116 CRC cells with isogenic partner
`cells carrying individual and combinatorial genetic deletions
`of two major human DNA methyltransferases (Figure 1A) [14].
`
`Editor: Jeannie T. Lee, Massachusetts General Hospital, United States of America
`
`Received April 12, 2007; Accepted July 31, 2007; Published September 21, 2007
`
`A previous version of this article appeared as an Early Online Release on July 31, 2007
`(doi:10.1371/journal.pgen.0030157.eor).
`
`Copyright: Ó 2007 Schuebel et al. This is an open-access article distributed under
`the terms of the Creative Commons Attribution License, which permits unrestricted
`use, distribution, and reproduction in any medium, provided the original author and
`source are credited.
`
`Abbreviations: CRC, colorectal cancer; DAC, 5-aza-29-deoxycytidine; DKO, double
`knockout; MSP, methylation-specific PCR; RT-PCR, reverse transcriptase PCR;
`TSA, trichostatin A
`
`* To whom correspondence should be addressed. E-mail: kornels@jhmi.edu
`(KES); sbaylin@jhmi.edu (SBB)
`
`[ These authors contributed equally to this work.
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`Author Summary
`
`Loss of gene expression in association with aberrant accumulation of
`5-methylcytosine in gene promoter CpG islands is a common feature
`of human cancer. Here, we describe a method to discover these genes
`that permits identification of hundreds of novel candidate cancer
`genes in any cancer cell line. We now estimate that as much as 5% of
`colon cancer genes may harbor aberrant gene hypermethylation and
`we term these the cancer ‘‘promoter CpG island DNA hyper-
`methylome.’’ Multiple mutated genes recently identified via cancer
`resequencing efforts are shown to be within this hypermethylome
`and to be more likely to undergo epigenetic inactivation than genetic
`alteration. Our approach allows derivation of new potential tumor
`biomarkers and potential pathways for therapeutic intervention.
`Importantly, our findings illustrate that efforts aimed at complete
`identification of the human cancer genome should include analyses
`of epigenetic, as well as genetic, changes.
`
`Importantly, in the DNMT1(/)DNMT3B(/) double knockout
`(DKO) HCT116 cells, which have virtually complete loss of
`global 5-methylcytosine, all previously individually examined
`hypermethylated genes lacking basal expression in wild-type
`cells undergo promoter demethylation with concomitant
`gene re-expression [10,14–16]. By stratifying genes according
`to altered signal intensity on a 44K Agilent Technologies
`array platform, we observe a unique spike of gene expression
`increases in the DKO cells when compared to the isogenic
`wildtype parental cells, or isogenic cell lines in which DNMT1
`or DNMT3B have been individually deleted and which harbor
`minimal changes in DNA methylation (Figure 1B). This
`minimal change in the DNMT1(/)cells may, in part, be due
`to recently identified alternative transcripts arising from the
`DNMT1 locus [17,18].
`We tested our approach using a pharmacologic strategy
`based on our previous approach [10], but now markedly
`modified to provide whole-transcriptome coverage, to identify
`silenced hypermethylated genes in any cancer cell line. For
`densely hypermethylated and transcriptionally inactive genes,
`the DNA demethylating agent 5-aza-29-deoxycytidine (DAC)
`has a well established capacity to induce gene re-expression
`[19,20]. On the other hand, for these same genes, the class I and
`II histone deacetylase inhibitor, trichostatin A (TSA) will not
`alone induce reexpression [10,21]. We now use this lack of TSA
`response for such genes to provide a new informatics filter to
`
`Gene Hypermethylation and Mutations
`
`identify the majority of DNA hypermethylated genes in cancer.
`After treatment of HCT116 cells with either DAC or TSA
`(Figure 1C), we identified a zone in which gene expression did
`not increase with TSA (,1.4-fold) and displayed no detectable
`expression in mock-treated cells. Within this zone, we observed
`a characteristic spike of DAC-induced gene expression that
`virtually completely encompasses the genes with increased
`expression in DKO cells (compare yellow spots in Figure 1D
`with blue spots in Figure 1B). This gene spike is absolutely
`dependent upon analysis of only genes that fail to respond to
`histone deacetylase inhibition, underscored by a cluster
`analysis that shows the close relationship between genes in
`DKO- and DAC-treated cells with a separate grouping of gene-
`expression changes after TSA treatment alone or in single
`knockouts (Figure 1E). These data confirm previous studies
`covering much less of the genome, and using only treatment of
`cells with DAC and TSA together, in which genes with dense
`CpG islands that were reexpressed by TSA harbored only
`partial or no detectable hypermethylation [10,21].
`Importantly, a similar spike of gene expression increases
`could be seen in five additional human CRC cell lines, SW480,
`CaCO2, RKO, HT29, and COLO320 (Figure 2A), as well as cell
`lines derived from lung, breast, ovary, kidney, and brain
`(unpublished data), confirming that this approach works
`universally in cancer cell lines and identifies overlapping
`gene sets (Figure 2C). However, it is important to note that—
`possibly because DAC incorporates into the DNA of dividing
`cells, and our treatments were performed for only 96 h—
`sensitivity for detecting the gene increases in the pharmaco-
`logical approach is reduced in HCT116 cells compared to that
`seen in DKO cells (Figure 1D). To address the sensitivity with
`which our new array approach identifies CpG island hyper-
`methylated genes, we first examined 11 genes known to be
`hypermethylated, completely silenced and reexpressed after
`DAC treatment in HCT116 cells (Figure 3A). All tested genes
`remained within the TSA nonresponsive zone (Figure 3B), and
`the direction of expression changes correlated well in DAC
`treated and DKO cells (Figure 3C). Importantly, for the DAC
`increase, five of the guide genes (45%) increased 2-fold or
`more and three more genes, or a total of 73%, increased 1.3-
`fold or more (Figure 3D). We estimate, then, that we can detect
`over 70% of DNA hypermethylated genes in a given cancer
`cell line and we test this hypothesis in studies directly below.
`
`Figure 1. Approach for Identification of the Human Cancer Cell Hypermethylome in HCT116 CRC Cells
`(A) RNA from the indicated cell lines was isolated, labeled, hybridized, scanned, and fluorescent spot intensities normalized by background subtraction
`and Loess transformation using Agilent Technologies 44K human microarrays. Parental wild-type HCT116 cells (WT) and isogenic knockout counterparts
`for DNA methyltransferase 1 (DNMT1/) or 3b (DNMT3B/) are compared in our study. DKO cells are doubly deficient for both DNMT1 and DNMT3B.
`(B) Gene-expression changes in HCT116 cells with genetic disruption of various DNA methyltransferases. A 3-D scatter plot indicating the gene-
`expression levels in HCT 116 cells with genetic disruption of DNMT1 (x-axis), DNMT3B (z-axis), and both DNMT1 and DNMT3B (DKO; y-axis) in fold scale.
`Individual gene-expression changes are in black with the average for three experiments (red spots) or from an individual experiment (blue spots) for
`those genes in DKO cells with greater than 4-fold expression change.
`(C) HCT116 cells were treated with 300 nM TSA for 18 h or 5 lM DAC for 96 h and processed as described above.
`(D) Gene-expression changes for HCT116 cells treated with TSA (x-axis) or DAC (y-axis) are plotted by fold change. Yellow spots indicate genes from
`DKO cells with 2-fold changes and above. Notice the loss of sensitivity when compared to gene-expression increases seen in DKO cells (80% of genes
`greater than 4-fold in the DKO cells now becomes greater than 1.3-fold in DAC-treated cells). Green spots indicate randomly selected genes verified to
`have complete promoter methylation in wild-type cells, reexpression in DKO cells and after DAC treatment, while red spots indicate selected genes that
`were identified as false positives (See Figures 4, 6, and 7 for validation results). Blue spots indicate the location of the 11 guide genes—previously
`shown to be hypermethylated and completely silenced in HCT 116 cells—used in this study (see Figure 3 for description). A distinct group of genes,
`including five of 11 guide genes, displays increases of greater than 2-fold after DAC treatment but no increase after TSA treatment. These genes form
`the top tier of candidate hypermethylated genes as discussed in the text.
`(E) Relatedness of whole-transcriptome expression patterns identified by dendrogram analysis. Individual single genetic disruption of DNMT1 and
`DNMT3B, DKO and DAC treatment, and TSA treatment each form three distinct categories of gene expression changes.
`doi:10.1371/journal.pgen.0030157.g001
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`Gene Hypermethylation and Mutations
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`Figure 2. Characterization of the Human Cancer Cell Hypermethylome in Different Human CRC Cell Lines
`(A) Gene-expression changes for the indicated cells treated with TSA (x-axis) or DAC (y-axis) are plotted by log-fold change, and individual genes are
`shown in black.
`(B) Validation of the DNA hypermethylome. The characteristic spike of hypermethylated genes defined by treatment of cells with DAC or TSA consists of
`two tiers, with distinct features. The top tier of genes was identified as a zone in which gene expression did not increase with TSA (,1.4 fold) and
`displayed no detectable expression in wild-type cells, but increased greater than 2-fold with DAC treatment. The next tier of genes was identified as a
`cluster of genes for which expression changes of TSA and wild type were identical to those in the top tier, but increased between 1.4-fold and 2-fold
`with DAC treatment. Gene expression validation by RT-PCR and MSP indicated a validation frequency of 91% for top-tier genes in HCT116 cells,
`including genes that increased in DKO cells by greater than 2-fold. Next-tier genes in HCT116 cells were confirmed at a frequency of 49%, and in the
`SW480 top tier, with a frequency of 65%.
`(C) Shared candidate hypermethylated genes in CRC cell lines. We identified a total of 5,906 unique genes in all six cell lines with expression changes
`falling within the criteria of top- or next-tier categories. Overlaps in gene expression changes among two, three, four, five, or six cell lines are indicated;
`these range from 1,414 genes shared among two cell lines to 78 genes that were shared among all six cell lines.
`doi:10.1371/journal.pgen.0030157.g002
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`Validating the Methylation Status of Candidate Genes
`Derived from the Screening Approach
`Based on the sensitivity differences observed between
`DKO- and DAC -induced gene increases (compare Figure
`1B and D; also Figure 3B and 3C) and behavior of the guide
`genes in the array platform, we designated, within the TSA-
`negative zone, a top tier (2-fold increase or above) and a next
`tier of genes (increasing between 1.4- and 2-fold) to identify
`hypermethylated cancer genes (Figure 2B). Importantly, we
`introduced an additional filter for selecting genes from these
`zones based on their having no basal expression in untreated
`
`cells, since this full lack of transcription is characteristic of
`promoter CpG island methylated genes in cell culture.
`Indeed, based on these selection criteria, in HCT116 cells,
`32 of 35 (91%, Figure 4) of randomly chosen CpG island–
`containing genes spanning the top-tier response zone of 532
`genes (Figure 5), and 31 of 48 such SW480 cell genes (65%,
`Figure 6) from among 318 top tier genes proved to be CpG
`hypermethylated as measured by methylation-specific PCR
`(MSP) [22], and silenced in the cell line of origin as measured
`by reverse transcriptase PCR (RT-PCR). We also examined the
`efficiency of discovery for hypermethylated genes in the next
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`Figure 3. Guide Genes Used in This Study
`(A) Gene names, Agilent Technologies probe name, Genbank accession number, and references for the 11 guide genes previously shown to be
`hypermethylated and completely silenced in HCT116 cells.
`(B, C) Blue spots and gene names indicate the location of the 11 guide genes in a plot of TSA (x-axis) versus DAC (y-axis) gene expression changes on a
`log scale (B) or fold-change (C) scale. Five of 11 guide genes, circled in green, display increases of greater than 2-fold after DAC treatment but no increase
`after TSA treatment and these same genes have greater than 3-fold increases in DKO cells (green circle)
`(D) Direct comparison of guide genes in DKO and DAC plots. A distinct group of five guide genes, indicated by a green circle, showing greater than 3-
`fold expression changes in DKO cells and greater than 2-fold in DAC-treated cells, define the upper tier of candidate hypermethylated genes as
`discussed in the text. Another three genes increased 1.3-fold, and three failed to increase with DAC treatment, allowing criteria for the next tier of gene
`expression to be established as described in the text.
`doi:10.1371/journal.pgen.0030157.g003
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`tier of DAC-treated HCT116 cells. Of the 1,190 genes
`identified in this region, 17 of 35 (49%) randomly selected
`genes containing a CpG island were hypermethylated with
`concordant gene silencing (Figure 7). Our verification rates
`then demonstrate around 65% efficiency of our approach,
`which is close to our original estimate and which is excellent
`compared to previous screens for identifying new cancer
`hypermethylated genes [6,23]. With this level of verified
`
`hypermethylation, we calculate that the hypermethylome in
`HCT116 cells consists of an estimated 1,067 genes and an
`estimated 579 genes for the SW480 cells (See Table S1 for a
`detailed description of calculations). The hypermethylome
`would be estimated to range from 532 genes in CaCO2 to
`1,389 genes in RKO cells (Table S1).
`We next asked whether our top and next-tier regions truly
`enriched for hypermethylated genes by examining a randomly
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`Gene Hypermethylation and Mutations
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`Figure 4. Verification of the HCT116 Top Tier Hypermethylome
`List of HCT116 candidate hypermethylated genes selected for verification of expression (by RT-PCR of HCT116 and DKO cells) and promoter methylation
`(by MSP of HCT116 and DKO cells) status. Gene descriptions are indicated on the left side of the panel and gene names are shown next to the PCR
`results. Water (RT-PCR and MSP),
`in vitro methylated DNA (for MSP), and actin beta (ACTB) were used as controls for each individual gene;
`a representative sample is shown. Green arrows identify genes that verified the array results, red arrows those that did not.
`doi:10.1371/journal.pgen.0030157.g004
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`selected subset of 22 control genes located outside these
`zones. These genes were located in the responsive TSA zones
`(Zones 1 and 2, Figure S1A) or below the threshold of DAC
`responsiveness in the TSA nonresponsive zone (Zone 3, Figure
`S1A) in HCT116 cells. Of the tested genes, only 9% (2 of 22,
`Figure S1B) showed detectable methylation with concomitant
`gene silencing, confirming the specificity of our approach and
`validating the criteria we used to establish the top and next-
`tier approach. We can then predict that for cancer cell lines,
`with use of our filters, ;90% of promoter CpG island DNA
`methylated genes lie in the negative TSA-responsive zone.
`A fundamental question in cell culture–based approaches is
`whether they identify genes that are targets for inactivation in
`
`primary tumors. To address this, 20 CpG island containing
`genes from the verified gene lists were randomly selected from
`the HCT116 top tier (17 genes), HCT116 next tier (two genes),
`or SW480 top tier (one gene) and analyzed for methylation in
`a panel of CRC cell
`lines. All of the tested genes were
`hypermethylated in two or more cell lines (Figure 8). We then
`examined the status of these 20 genes in a panel of 20 to 61
`primary colon cancers and 20 to 40 normal-appearing colon
`tissue samples obtained from cancer-free individuals. Most of
`the genes (65%) were completely unmethylated or rarely
`methylated in the normal colonic tissue samples, but were
`methylated in a vast majority (86%) of the primary tumors
`(Figure 8). Of the 20 genes analyzed, 13 genes (65%) satisfied
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`Gene Hypermethylation and Mutations
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`mutations in humans lead to a plethora of craniofacial
`anomalies and premature ovarian failure [33]. We find both
`of these genes to be frequently DNA hypermethylated in a
`panel of colorectal cell lines (five of nine cell lines for NEURL
`and seven of nine for FOXL2, Figure 9A and 9C), and bisulfite
`sequencing revealed methylation of all CpG residues in the
`central CpG island regions of both genes in HCT116 and RKO
`cell lines, with complete demethylation in DKO cells (Figure 9B
`and 9D). For both genes, this hypermethylation perfectly
`correlated with loss of basal expression and ability to reexpress
`the genes with DAC treatment (Figure 9A and 9C). Impor-
`tantly, promoter methylation of both genes, as assessed by
`bisulfite sequencing (Figure 9B and 9D) is absent in normal
`human colon or rectum, but frequent in primary colon cancers
`(Figure 9E and 9F), suggesting that hypermethylation arose as a
`cancer-specific phenomenon, although slight methylation was
`observed at the FOXL2 locus in normal tissue from aged
`patients (unpublished data). Finally, the pattern for hyper-
`methylation of the FOXL2 and NEURL genes in cell culture fit
`with a biology important to a subset of colon cancers. As many
`as one in eight colorectal cancers, predominantly those from
`the right side of the colon, harbor a defect in mismatch-repair
`capacity [34,35], primarily due, in nonfamilial cancers, to
`inactivation of MLH1 by epigenetic mechanisms [36]. Such
`tumors belong to a group with high frequency of hyper-
`methylated gene promoters [37,38]. The hypermethylation of
`FOXL2 and, especially, NEURL, aggregate with these tumor
`types not only among the colon cancer cell lines (HCT116,
`DLD1, LoVo, RKO, and SW48), but also when analyzed in a
`series of primary human colon cancers (Fisher’s exact test
`value of 0.024 for FOXL2 and 0.001 for NEURL, Figure 9G).
`Initial in vitro studies suggest that both FOXL2 and NEURL
`might possess tumor-suppressor activity. When overex-
`pressed in colon cancer cell lines, full-length FOXL2 and
`NEURL (Figure 10A and 10C), generate a 10-fold and 20-fold
`reduction, respectively, in colony growth of HCT116 cells
`(Figure 10C), with surviving clones having severely depleted
`size (Figure 10B), comparable to results obtained with the
`bona fide tumor suppressor p53 (Figure 10F). Similar results
`were seen in RKO and DLD1 cells (Figure 10D and 10E), both
`of which have complete gene silencing at the FOXL2 and
`NEURL loci. While the precise molecular mechanisms for the
`growth suppression remains to be determined, Notch signal-
`ing has recently been shown to play an important role in
`differentiation of intestinal crypt cells where deletion of the
`Notch effector molecule RBPJj or treatment with a highly
`selective c-secretase inhibitor was found to be sufficient for
`conversion of crypt cells to goblet cells [28,29]. Similarly, the
`closely related FOXL2 transcription factor family member
`FOXL1 has recently been shown to play a role in epithelial–
`mesenchymal transition of the intestinal epithelium [39].
`
`Comparison of Newly Identified DNA Hypermethylated
`Genes to Mutated Genes Identified from Sequencing of
`Cancer Genomes
`While it is clear that genetic and epigenetic mechanisms
`are both important to initiation and progression of human
`tumorigenesis, the relative contributions of each of these
`alterations need to be clarified on a global basis. Studies of
`classic tumor suppressor genes such as VHL in renal cancer
`and MLH1 in colon cancer indicate that important cancer
`genes can have an incidence of inactivation by either genetic
`
`Figure 5. Distribution of Verified HCT116 Top-Tier genes
`Green spots show the location of individual genes with names indicated
`in blue. The top tier of gene-expression changes within the spike shown
`in Figure 1D has been magnified, and values for DAC and TSA expression
`changes are shown in log scale.
`doi:10.1371/journal.pgen.0030157.g005
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`criteria for ‘‘tumor-specific methylation’’ with high-frequency
`methylation in cell
`lines,
`low (,5%) or undetectable
`methylation in normal colon, and frequent methylation in
`primary tumor samples (Figure 8). The efficiency of our
`strategy suggests a discovery rate of approximately one in two
`for identification of hypermethylated genes in cell lines and
`approximately one in three for identification of cancer-
`specific hypermethylated genes. Our estimate of approxi-
`mately 400 hypermethylated genes per primary tumor now
`can be matched with predictions of Costello et al. [5] for
`hypermethylation of CpG islands, based on screening with
`Restriction Landmark Genomic Scanning approaches.
`
`Validating Potential Biologic Relevance of Newly
`Identified Genes
`We next tested some parameters for biological significance
`of two of the genes harboring tumor-specific methylation for
`their likely importance in primary colon cancers. One, the
`neuralized homolog (Drosophila) (NEURL) gene, is located in a
`chromosome region with high deletion frequency in brain
`tumors [24], and its product has been identified as a ubiquitin
`ligase required for Notch ligand turnover [25–27]. Activation
`of this key developmental pathway influences cell-fate deter-
`mination in flies and vertebrates [28,29] and activation of
`Notch, through unknown mechanisms, is thought to play an
`inhibitory role in normal differentiation during colorectal
`cancer [30]. The second gene, FOXL2, belongs to the forkhead
`domain–containing family of transcription factors implicated
`in diverse processes including establishing and maintaining
`differentiation programs [31]. Intriguingly, this gene is
`essential for proper ovarian development [32] and germline
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`Gene Hypermethylation and Mutations
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`Figure 6. Verification of the HCT116 Next Tier Hypermethylome
`Genes were selected for verification of expression (by RT-PCR of HCT116 and DKO cells) and promoter methylation (by MSP of HCT116 and DKO cells)
`status. Gene names are indicated on the left side of the panel and gene abbreviations are shown next to the PCR results. Water (RT-PCR and MSP),
`in vitro methylated DNA (for MSP), and actin beta (ACTB) were used as controls for each individual gene; a representative sample is shown. Green arrows
`identify genes that verified the array results, red arrows those that did not as discussed in the text.
`doi:10.1371/journal.pgen.0030157.g006
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`or epigenetic mechanisms [36,40]. However, a genome-wide
`analysis to query such relationships has not been performed.
`In a recent genome-wide sequencing of cancer genes,
`[3] observed that newly discovered gene
`Sjo¨ blom et al.
`mutations in colon and breast cancers generally had a low
`incidence of occurrence, with 90% of the genes identified
`harboring a mutation frequency of less than 10%. Further-
`more, a typical patient’s colon or breast tumor was estimated
`to have an average of only 14 mutations and there appeared
`to be little overlap between individual tumors for the newly
`discovered mutations [3]. These low frequencies raise the
`
`question whether alternative mechanisms might account for
`inactivation of these genes in additional tumors. Obviously,
`the much higher number of candidate hypermethylated genes
`we now identify in individual tumors suggests that this
`epigenetic change might provide an alternative inactivating
`route to mutations for many tumor suppressor genes. We
`now show that screening tumors for both genetic and
`epigenetic changes indicates that this is the case.
`We first located the 189 newly identified, mutated cancer
`(CAN) genes, described by Sjo¨ blom et al. [3], within the top
`and next tiers of our colorectal cancer cell
`line hyper-
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`Gene Hypermethylation and Mutations
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`Figure 7. Verification of the SW480 Top-Tier Hypermethylome
`Genes were selected for verification of expression (by RT-PCR of SW480 and DAC-treated SW480 cells) and promoter methylation (by RT-PCR of SW480
`and DAC-treated SW480 cells) status. Full gene names are indicated on the left side of the panel and abbreviated gene names are shown next to the
`PCR results. Water (RT-PCR), in vitro methylated DNA (for MSP), and actin beta (ACTB) were used as controls for each individual gene; a representative
`sample is shown. Green arrows identify genes that verified the array results, red arrows those that did not as discussed in the text.
`doi:10.1371/journal.pgen.0030157.g007
`
`methylome and found 56 genes present in these zones in one
`or more of the cell lines. Of these, 45 contained CpG islands.
`Twenty-six of these 45 genes (58%), similar to the verification
`rate for all candidate genes identified as discussed above,
`proved to be hypermethylated in at least one of the six cell
`lines, and were selected for further study. Importantly, exactly
`
`half (13 of 26 genes) of these genes were expressed at high
`levels (Figure 11A) and were not methylated in normal colon
`(Figure 11B) but were methylated in primary CRC tumors
`(Figure 11C), giving a frequency of 50% for identification of
`tumor-specific methylation when starting with genes harbor-
`ing cell
`line methylation. We also randomly selected, for
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`September 2007 | Volume 3 | Issue 9 | e157
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`Geneoscopy Exhibit 1037, Page 9
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`

`

`Gene Hypermethylation and Mutations
`
`Figure 8. Comparison of Hypermethylation Frequencies in Human Tumor Samples
`Methylation analysis of verified hypermethylome genes in human tissue samples. Twenty genes from the verified gene lists were randomly selected from
`the HCT116 top tier (BOLL, DDX43, DKK3, FOXL2, HOXD1, JPH3, NEF3, NEURL, PPP1R14A, RAB32, STK31, and TLR2), HCT116 next tier (SALL4 and TP53AP1),
`or SW480 top tier (ZFP42) and analyzed for methylation in CRC cell lines (white columns), normal colon (red columns), or primary tumors (green columns).
`Percentage of methylation is indicated on the y-axis, and the abbreviated gene name on the x-axis. We tested at least six different cell lines, 16 to 40
`colonic samples from noncancer patients, and between 18 and 61 primary CRC samples for each gene.
`doi:10.1371/journal.pgen.0030157.g008
`
`verification of methylation and expression status in cell lines,
`CAN genes that fell primarily in zone 3 of the microarray, that
`is, within the TSA-negative zone but below the 1.4-fold cutoff
`for stimulation by DAC. As seen earlier for other randomly
`selected genes in this region, these randomly selected CAN
`genes had a significantly reduced (four of 15, or 27%)
`frequency of methylation as compared to the 56 top and
`next-tier CAN genes discussed above (Figure S1C). Interest-
`ingly, however, this rate is much more similar to that for the
`well-characterized hypermethylated guide genes (;30% as
`shown in Figure 3A–3C) than for the other randomly selected
`zone 3 genes (9%, compare Figure S1B and S1C), perhaps
`indicating the importance of epigenetic inactivation of these
`mutated genes. Indeed, relevant to this point, for the majority
`of the examined CAN genes within the hypermethylome
`region, the incidence of hypermethylation is strikingly higher
`than that for mutations (Figure 11D). Thus, unlike for the
`mutations in the in