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Computational Molecular Biology
7
They also found the cancer-specific DMRs between
colon cancer and matched normal mucosa overlap
DMRs among three normal tissues (brain, liver and
spleen) significantly. Furthermore, Hansen et al.
identified colon cancer-specific differentially
DNA-methylated regions that may contribute to tumor
heterogeneity (Hansen et al., 2011). Identification of
more cancer-specific abnormal methylation markers
should be beneficial for mining of therapeutic and
diagnostic indicators as DNA methylation is
somatically heritable and reversible.
High-throughput methylation profiling technologies
makes it possible to quest the methylation variations
among multiple cancers. Illumina Human Methylation
27 BeadChip allows researchers to interrogate the
methylation status of more than 27000 highly
informative CpG sites spanning 14,475 genes
including 1,126 cancer-related genes (He et al., 2007).
This high-density panel lets researchers profile up to
12 samples in parallel, which makes it adequate for
case-control studies. Thus, this technology has been
widely used to profile the methylation patterns of
cancers and their normal control tissues (Calin and
Croce, 2006; Wang et al., 2007; Yoon and De Micheli,
2005; Weber et al., 2005).
However, there has not been a comprehensive
understanding of the location and function of DMRs
among different cancers (C-DMRs). Thus in this study,
we focused on following two questions by analyzing
the methylation states of more than 27,000 CpG sites
located in gene promoters in six different cancers and
five corresponding normal controls. First, where is the
methylation variation among multiple cancers? Taking
into account DMRs among normal tissues (T-DMRs)
which may play a role in cellular identity and the
regulation of tissue-specific genome function (Rakyan
et al., 2008), we analyzed the relationships between
C-DMRs and T-DMRs and identified the
bona fide
C-DMRs. Second, what are function roles of these
methylation variations among multiple cancers? To
this end, we carried out a comprehensive study in
regulatory mechanism, functional annotation and
protein interactions on the genes related with
bona
fide
C-DMRs.
1 Results
1.1 DNAmethylation discriminates human tissue types
In order to analyze the methylation patterns in
different human cancers and their corresponding
normal tissue, we obtained methylation states of
27543 CpGs in 297 samples from six cancers and five
matched normal control tissues (Materials and
Methods). To view the methylation patterns in
different cancers and tissues, we performed
hierarchical clustering using Euclidean distance. The
hierarchical clustering in all 297 samples shows the
similar methylation pattern among the samples
representing the same tissue or cancer. The
hierarchical clustering based on the mean methylation
levels among all the replicate samples per
tissue/cancer also perfectly discriminated among
different tissue types, regardless of the normal or
disease status (Figure 1A).
For example, there are three main methylation clusters:
the first one encompassing the normal plasma,
multiple myeloma cancer and plasma cell leukemia,
the second one encompassing normal brain and
Glioblastoma cancer, and the third one encompassing
normal prostate and prostate cancer. Exceptionally, we
observed the clustering of colorectal cancer and breast
cancer, and the clustering of normal colorectal and
normal breast. The possible interpretation for this
observation could be the previous finding that
colorectal cancer and breast cancer own the common
susceptibility genes (Garcia-Patino et al., 1998) and
aberrant methylation of the common suppressor genes
(Agrawal et al., 2007). The hierarchical clustering
using Pearson correlation gives exactly the same
observations motioned above. It is indicated that the
methylation patterns among different states of the
same tissue are more similar than those among
different tissues.
1.2 The similarity of methylation pattern between
cancer and corresponding normal control
We explored the similarity of methylation patterns of
CpG sites between cancer and corresponding normal
control globally. It is interesting that multiple
myeloma cancer and plasma cell leukemia showed
obvious lower methylation levels than other cancers,
and their corresponding normal tissue plasma also
showed lower methylation levels than other normal
Computational
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