Basic HTML Version
Computational Molecular Biology
9
tissues (Figure 1B). The similar distribution of
methylation levels between cancer and the
corresponding normal tissue is revealed.
Further analysis on the methylation of CpGs in CpG
islands and those out of CpG islands showed the same
result. The methylation levels of CpGs in CpG islands
are lower than those of CpGs out of CpG islands. For
the CpGs in CpG islands, the methylation levels in
cancers were slight higher than those in normal tissues
(Fig. 1C), which is consistent with the previous
reports of hypermethylation of the CpG islands in
promoter regions (Koga et al., 2009). Then we
mapped the methylation levels upstream of the
transcription start site (TSS). It is shown that
methylation level increased gradually with increasing
distance upstream of TSS in all cancers/tissues
(Figure 1 D). All these results revealed that cancers
have similar methylation levels with their
corresponding normal tissues. Thus, it is necessary to
take account of the methylation difference among
tissues when we study the methylation difference
among different cancers.
1.3 Identification of differentially methylated sites
among multiple cancers
In order to mine the cancer-specific methylation
markers, we used QDMR to identify the DMSs among
multiple cancers (C-DMSs) and DMSs among
multiple normal tissues (T-DMSs). QDMR assigns
each CpG site two entropy values. The entropy
representing the methylation difference across six
cancers ranges from 0.187 to 19.057, while another
one representing the methylation difference across
five normal tissues ranges from 0.194 to 17.673
(Figure 2 A and B). The lower the entropy is, the
greater the methylation difference across cancers is.
Based on the quantitative methylation difference, all
CpGs were classified as 9645 C-DMSs and 17898
Cs-UMSs by the threshold for six samples given in
QDMR (Figure 2A). By another threshold for five
normal tissues, all CpGs were classified as 8480
T-DMSs and 19063 T-UMSs (Figure 2B). The number
of C-DMSs is more than that of T-DMSs, which
indicates there are more CpGs with differential
methylation across multiple cancers. Most of C-DMSs
show lower methylation levels in multiple myeloma
cancer and plasma cell leukemia than other types of
cancer (Figure 2C). Coincidentally, most of T-DMSs
showed lower methylation levels in plasma than other
normal tissues (Figure 2D). It is suggested that
C-DMSs and T-DMSs possess the similar methylation
pattern among different cancers/tissues. Moreover,
both of Cs-UMSs and T-UMSs show hypomethylation
in all cancers/tissues (Figure 2 E and F).
1.4 Selection of
bona fide
C-DMSs
Further analysis revealed that 57% (5486/9645) of
C-DMSs are also identified as T-DMSs, compared to
only 31% (8480/27543) expected by chance
(P<0.0001, Figure 3A). Thus, T-DMSs should be
considered when we identify the
bona fide
C-DMSs.
Here, the
bona fide
C-DMSs were defined as the CpG
sites identified as C-DMSs across cancers but as
T-UMSs across normal tissues. Using these criteria,
we selected 4159
bona fide
C-DMSs among six
cancers. These CpG have different methylation among
cancers than other tissue, and may be cancer-specific
methylation markers. The function of the genes related
with these
bona fide
C-DMSs may be helpful for
understanding the roles of DNA methylation in
cancers.
1.5 The function of genes with differential methyl-
lation sites
In order to explore the function of the genes with
differential methylation sites, we carried out
functional enrichment analysis for the genes related
with 4159
bona fide
C-DMSs among six cancers using
DAVID (http://david.abcc.ncifcrf.gov/ ). It is revealed
that the genes related with
bona fide
differentially
methylated sites are enriched with the functions
related with cancer such as cell membrane
components, cell adhesion, cell migration, immune
response and cell proliferation (Table 1). And these
genes are enriched in some important signaling
pathway in cancer. Twenty-eight genes are targeted by
hsa-miR-323 which participates in tumorigenesis
(Plaisier et al., 2012). It is indicated that miRNA may
be a potential regulator of dynamic DNA methylation
and may be the epigenetic marks for multiple cancers.
These results reveal the potential roles of DNA
methylation in cancer by regulating the cancer genes.
Computational
Molecular Biology