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Computational Molecular Biology
2013, Vol.3, No.2, 6-15 http://cmb.sophiapublisher.com
Research Report
Open Access
Identification of the
Bona fide
Differentially Methylated Gene Markers among
Cancers
Hongbo Liu
1
, Xiaojuan Liu
2
, Zhe Li
3
, Yan Zhang
1
1. College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China
2. Department of Rehabilitation, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
3. College of Pharmacy, Harbin Medical University, Harbin 150081, China
Corresponding Author email: yanyou1225@gmail.com;
Author
Computational Molecular Biology, 2013, Vol.3, No.2 doi: 10.5376/cmb.2013.03.0002
Copyright
© 2013 Liu et al. This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use,
distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
DNA methylation plays important roles in the development of cancers. Previous studies have identified the differentially
methylated sites (DMSs) between cancer and normal control. However, the methylation variations across multiple cancers have not
been revealed. In this study, we identified DMSs among six human cancers (C-DMSs) and DMSs among five normal control tissues
(T-DMSs). It is revealed that C-DMSs are highly overlapped with T-DMSs. By excluding the T-DMRs from C-DMRs, 4159
bona
fide
C-DMSs were selected as methylation variations across multiple cancers. Further analysis confirmed the roles of
bona fide
C-DMSs in regulation of cancer-related gene expression differences. Moreover, the genes related with these
bona fide
C-DMSs
showed enrichment in the biological processes such as cell membrane components, cell adhesion, cell migration, immune response
and cell proliferation, and also the pathways in cancer and bladder cancer. In addition, twenty-eight genes are targeted by
hsa-miR-323 which participates in tumorigenesis. In the end, we identified potential cancer-related genes by extracting protein
interaction sub-network. This study provides a new framework for mining the potential cancer-specific methylation markers and
oncogenes.
Keywords
DNA methylation;
bona fide
C-DMSs; Methylation variation; Ancer-specific methylation markers
Background
DNA methylation plays an important role in the
development of cancers (Esteller, 2008). Cancer is a
complex collection of diseases that differ on basis of
the tissue of origin. Most of cancer deaths are due to
the metastasis of cancer cells from its original site to
another area of the body (Rodenhiser, 2009; Bhatia et
al., 2012). Besides genetic contributors to metastasis,
there are also epigenetic alterations involved in
cancer metastasis. DNA methylation of promoters in
some genes take part in a wide variety of essential
molecular pathways related with metastasis (Heng et
al., 2010). The recent study by Fang et al.
characterized the methylomes of breast cancers with
diverse metastatic behavior (Zhang et al., 2006).
However, the cancer-specific alterations and their
effects on carcinogenesis and metastasis remain
obscure.
The investigation of cancer-specific alterations in
DNA methylation enables the mining of the hallmarks
of human malignancies. Previous studies have
identified the differentially methylated regions (DMRs)
between cancer and normal control by bioinformatics
tools such MethMarker (Schuffler et al., 2009). For
instance, Costello et al. identified aberrantly
methylated CpG islands in tumors and tumor-type
specific methylation patterns (Costello et al., 2000). In
addition, further analysis about colon cancer by
Irizarry et al. proved the existence of methylation
alterations in CpG island shores (Irizarry et al., 2009).
Preferred citation for this article:
Liu et al., 2013, Identification of the
Bona fide
Differentially Methylated Gene Markers among Cancers, Computational Molecular Biology, Vol.3, No.2
6-15 (doi: 10.5376/cmb.2013.03.0002)
Received: 12 Jun., 2013
|
Accepted: 19 Jun., 2013
|
Published: 28 Oct., 2013
Computational
Molecular Biology