Universität zu Köln

Cheng, Chun-Pei, Kuo, I-Ying, Alakus, Hakan, Frazer, Kelly A., Harismendy, Olivier, Wang, Yi-Ching ORCID: 0000-0002-7694-2067 and Tseng, Vincent S. (2014). Network-based analysis identifies epigenetic biomarkers of esophageal squamous cell carcinoma progression. Bioinformatics, 30 (21). S. 3054 - 3062. OXFORD: OXFORD UNIV PRESS. ISSN 1460-2059

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Abstract

Motivation: A rapid progression of esophageal squamous cell carcinoma (ESCC) causes a high mortality rate because of the propensity for metastasis driven by genetic and epigenetic alterations. The identification of prognostic biomarkers would help prevent or control metastatic progression. Expression analyses have been used to find such markers, but do not always validate in separate cohorts. Epigenetic marks, such as DNA methylation, are a potential source of more reliable and stable biomarkers. Importantly, the integration of both expression and epigenetic alterations is more likely to identify relevant biomarkers. Results: We present a new analysis framework, using ESCC progression-associated gene regulatory network (GRN(escc)), to identify differentially methylated CpG sites prognostic of ESCC progression. From the CpG loci differentially methylated in 50 tumor-normal pairs, we selected 44 CpG loci most highly associated with survival and located in the promoters of genes more likely to belong to GRN(escc). Using an independent ESCC cohort, we confirmed that 8/10 of CpG loci in the promoter of GRN(escc) genes significantly correlated with patient survival. In contrast, 0/10 CpG loci in the promoter genes outside the GRN(escc) were correlated with patient survival. We further characterized the GRN(escc) network topology and observed that the genes with methylated CpG loci associated with survival deviated from the center of mass and were less likely to be hubs in the GRN(escc). We postulate that our analysis framework improves the identification of bona fide prognostic biomarkers from DNA methylation studies, especially with partial genome coverage.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Cheng, Chun-Pei UNSPECIFIED UNSPECIFIED UNSPECIFIED Kuo, I-Ying UNSPECIFIED UNSPECIFIED UNSPECIFIED Alakus, Hakan UNSPECIFIED UNSPECIFIED UNSPECIFIED Frazer, Kelly A. UNSPECIFIED UNSPECIFIED UNSPECIFIED Harismendy, Olivier UNSPECIFIED UNSPECIFIED UNSPECIFIED Wang, Yi-Ching UNSPECIFIED orcid.org/0000-0002-7694-2067 UNSPECIFIED Tseng, Vincent S. UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-424602
DOI:	10.1093/bioinformatics/btu433
Journal or Publication Title:	Bioinformatics
Volume:	30
Number:	21
Page Range:	S. 3054 - 3062
Date:	2014
Publisher:	OXFORD UNIV PRESS
Place of Publication:	OXFORD
ISSN:	1460-2059
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language DNA METHYLATION; POOR-PROGNOSIS; MESENCHYMAL TRANSITION; PROMOTER METHYLATION; ABERRANT METHYLATION; BREAST-CANCER; GENE; EXPRESSION; TUMOR; INFLAMMATION Multiple languages Biochemical Research Methods; Biotechnology & Applied Microbiology; Computer Science, Interdisciplinary Applications; Mathematical & Computational Biology; Statistics & Probability Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/42460