Most studies on DNA methylation in cancer have focused on a candidate gene approach where a tumor suppressor or previously reported methylated gene is tested in another type of cancer. Although a number of studies have attempted to detect additional gene targets, in general, the gene selection methodologies have not been sensitive enough to identify target genes with comparatively less time and labor. By developing a new tool to analyze gene promoters in combination with a relatively large expression microarray data set, it has been possible for the first time to identify a large number of target genes. In our experience, this is a major advance over previous empirical techniques that required excessive experimental effort and yielded only a few (<0.5%) cancer-specific methylated genes (12
). Our yield, based on a combination of re-expression arrays and promoter sequence pattern, provided a nearly 500-fold higher yield of genes harboring promoter methylation.
We found that 47% (82 of 175) of the genes tested in cell lines were methylated by bisulfite sequencing and/or MSP, and 65% (53 of 82) of these genes were methylated in primary tumors. Our results are consistent with previous studies (12
), where the frequency of methylation of any particular gene in primary tumors is generally less than that observed in cell lines. The discrepancy between the computationally and pharmacologically predicted (175) and experimentally (82) identified methylated genes in cell lines may be partially due to the analysis of limited regions (~200–300 bp for most of the genes) by bisulfite sequencing or MSP.
To compare the overall pattern of methylated CGIs among tumors, we tested 300 primary tumors of 13 different types with 8 frequently cancer-specific methylated genes identified from our approach. Pancreas, gastric, thyroid, and ovary cancers displayed relatively low levels of methylation. Colon, prostate, esophagus, and kidney tumors, however, displayed a much higher frequency of methylation overall. Some tumors within a type displayed high inherent levels of methylation, whereas others within the same tumor type displayed low levels (data not shown). The data are not consistent with chance variation from tumor to tumor because in the absence of heterogeneity, the variance of the methylation frequency would not be expected to be greater than the mean. Therefore, aberrant methylation of CGIs can be quantitatively different in individual tumors within a tumor type and more pronounced in particular tumor types.
We found cancer-specific and tissue-specific methylation events in different tissue types. For example, PAK3
cancer-specific methylation was found in esophagus, lung, cervix, head and neck, and bladder cancers with high frequency. PAK3
was also occasionally methylated in other normal tissues. PAK3
is located in the X chromosome; thus, it is likely that there will always be methylated signal in samples from female patients. However, we consider PAK3 as cancer-specific methylation as we also found high frequency of methylation in samples from male cancer patients. Like PAK3, some other genes showed either cancer-specific or tissue-specific methylation in multiple organs (). Although there have been reports of MCAM
overexpression in melanoma, we found a high frequency of MCAM promoter methylation in prostate cancer. Oncostatin M receptor (OSMR) showed cancer-specific methylation only in colon cancer and was previously shown to have a major functional role in breast and other cancers (30
). Liang et al. (32
) reported loss of expression of SSBP2
in 50% of myeloid leukemia cell lines and concluded that loss of SSBP2 expression may underlie the impaired differentiation seen in human myeloid leukemia. However, before this report, there was no reported mechanism for loss of expression of this DNA-binding protein. β4GalT-1
is constitutively expressed in all tissues, with the exception of the brain (33
), as a Golgi-resident protein. We found a high frequency of cancer-specific methylation of β4GalT-1
in esophagus, lung, colon, and prostate. NISCH
[imidazoline receptor antisera selected (IRAS)] was first isolated as an imidazoline-1 receptor candidate cloned by an IRAS cDNA approach (34
) and was independently shown to be an interacting partner for insulin receptor substrate 4 (35
). IRAS was recently reported to protect transfected PC12 cells from apoptosis (36
), whereas its mouse homologue, Nischarin, which lacks the NH2
-terminal PX domain, was identified as a cytosolic-interacting protein for α5
integrin and shown to inhibit cell migration by inhibiting the ability of PAK1 to phosphorylate substrates (37
). We found a high frequency of cancer-specific methylation of this gene in lung, head and neck, and gastric cancer. KIF1A
is a member of the KIF1/Unc104 family, and targeted deletion of the KIF1A
gene in mice causes accumulation of clear small vesicles in the cell body of neurons as well as marked neuronal death (39
). We report for the first time a high frequency of cancer-specific methylation of KIF1A
in majority of human tumors.
The frequency of methylation within a tumor type of the individual CGIs affected in at least three different tumor types is shown (). Some targets were methylated at a high frequency in one tumor type but infrequently in others (e.g., OSMR; ), whereas other targets (e.g., KIF1A
) were methylated at relatively high frequencies in the majority of tumor types. Thus, whereas some CGIs targets are shared by multiple tumor types, others are methylated in a tumor-type–specific manner. It has been documented that virtually all biochemical, biological, and clinical attributes are heterogeneous within human cancers of the same histologic subtypes (40
). Our data suggest that differences in the methylated genes in various tumors could account for a major part of this heterogeneity.
Like any global genomic and epigenomic approach, our study has limitations. First, we were not able to test all the known and newly discovered methylated genes in all the 13 types of cancer included in this study. Second, although mosaic methylation occurred in most of the cases, focal methylation for some genes was also reported, and methylation in 5′ untranslated regions would not be detectable by the methods we used. Future studies using a combination of different technologies will be able to address these issues.
The results of this study inform future cancer methylome discovery effort in several important ways:
A major technical challenge of such studies will be discerning cancer-specific methylation from the large number of tissue-specific methylated genes. In our study, using modified gene selection criteria in pharmalogical unmasking strategy, we identified 47% methylated genes in contrast to 10% to 20% by previous criteria. In the future, improvements in gene selection strategy for prediction of methylation-prone gene should result in less labor and less empirical experimentation.
Another technical issue is the development of high throughput assays for the analysis of large numbers of samples. In this study, we developed QMSP assay for eight novel cancer-specific methylated genes and similar real-time assays could be developed individually for newly identified methylated targets. Once a methylation target set is known for a particular cancer, or even if the entire cancer “methylome” is discovered, other genomic approaches such as chip arrays may facilitate large scale research and clinical efforts.
Although it is likely that studies of other solid tumor types will also identify a large number of methylated genes, it will be important to apply rigorous approaches to identify the specific methylated genes that have been selected for during tumorigenesis. Our modified approach can predict for cancer-specific methylated genes and reduce empirical testing.
There has been much discussion about which genes should be the focus of future efforts for methylation analysis. Our results suggest that many genes not previously implicated in cancer are methylated at significant levels and may provide novel clues to cancer pathogenesis.
Adding these data to previous reports, perhaps up to one third (~300 genes total) of the cancer methylome has now been discovered, compared with the identification of perhaps 200 mutated genes over the past 2 decades and recent genome-wide mutation analysis in primary tumors (41
). An emerging picture of genetic and epigenetic changes and their relationship is unraveling the biological networks responsible for human cancer. The genetic and epigenetic alterations in different cancer types are diverse (42
), and we and others previously found unique inverse relationships between genetic/epigenetic changes (27
). However, 26 genes obtained in the Vogelstein’s last mutation screening are also methylated in our study (41
). Ultimately, the epigenome of all cancer tissues will be mapped out even as we now approach a total molecular signature of cancer. According to Dr. Peter Jones (as reviewed in ref. 47
), each differentiated cell has a different epigenome. Our comprehensive analysis contributes greatly to the emerging epigenomic map of DNA methylation in the human genome. Additional studies using similar and complementary genomic strategies should yield further insights into the dynamics and hierarchy of epigenetic regulation during tumorigenesis. These data define the epigenetic landscape of major human cancer types, provide new targets for diagnostic and therapeutic intervention, and open fertile avenues for basic research in tumor biology.