Network-based analysis identifies epigenetic biomarkers of esophageal squamous cell carcinoma progression

Chun-Pei Cheng; I-Ying Kuo; Hakan Alakus; Kelly A Frazer; Olivier Harismendy; Yi-Ching Wang; Vincent S Tseng

doi:10.1093/bioinformatics/btu433

Network-based analysis identifies epigenetic biomarkers of esophageal squamous cell carcinoma progression

Bioinformatics. 2014 Nov 1;30(21):3054-61. doi: 10.1093/bioinformatics/btu433. Epub 2014 Jul 10.

Authors

Chun-Pei Cheng¹, I-Ying Kuo², Hakan Alakus³, Kelly A Frazer³, Olivier Harismendy¹, Yi-Ching Wang¹, Vincent S Tseng¹

Affiliations

¹ Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan, Moores Cancer Center, University of California San Diego, La Jolla, CA 92093, USA, Institute of Basic Medical Sciences, National Cheng Kung University, Tainan 701, Taiwan, Department of Pediatrics and Rady Children's Hospital, University of California San Diego, La Jolla, CA 92093, USA, Department of General, Visceral and Cancer Surgery, University of Cologne, Köln, Germany, Institute for Genomic Medicine, University of California San Diego, La Jolla, CA 92093, USA, Department of Pharmacology and Institute of Medical Informatics, National Cheng Kung University, Tainan 701, Taiwan Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan, Moores Cancer Center, University of California San Diego, La Jolla, CA 92093, USA, Institute of Basic Medical Sciences, National Cheng Kung University, Tainan 701, Taiwan, Department of Pediatrics and Rady Children's Hospital, University of California San Diego, La Jolla, CA 92093, USA, Department of General, Visceral and Cancer Surgery, University of Cologne, Köln, Germany, Institute for Genomic Medicine, University of California San Diego, La Jolla, CA 92093, USA, Department of Pharmacology and Institute of Medical Informatics, National Cheng Kung University, Tainan 701, Taiwan.
² Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan, Moores Cancer Center, University of California San Diego, La Jolla, CA 92093, USA, Institute of Basic Medical Sciences, National Cheng Kung University, Tainan 701, Taiwan, Department of Pediatrics and Rady Children's Hospital, University of California San Diego, La Jolla, CA 92093, USA, Department of General, Visceral and Cancer Surgery, University of Cologne, Köln, Germany, Institute for Genomic Medicine, University of California San Diego, La Jolla, CA 92093, USA, Department of Pharmacology and Institute of Medical Informatics, National Cheng Kung University, Tainan 701, Taiwan.
³ Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan, Moores Cancer Center, University of California San Diego, La Jolla, CA 92093, USA, Institute of Basic Medical Sciences, National Cheng Kung University, Tainan 701, Taiwan, Department of Pediatrics and Rady Children's Hospital, University of California San Diego, La Jolla, CA 92093, USA, Department of General, Visceral and Cancer Surgery, University of Cologne, Köln, Germany, Institute for Genomic Medicine, University of California San Diego, La Jolla, CA 92093, USA, Department of Pharmacology and Institute of Medical Informatics, National Cheng Kung University, Tainan 701, Taiwan Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan, Moores Cancer Center, University of California San Diego, La Jolla, CA 92093, USA, Institute of Basic Medical Sciences, National Cheng Kung University, Tainan 701, Taiwan, Department of Pediatrics and Rady Children's Hospital, University of California San Diego, La Jolla, CA 92093, USA, Department of General, Visceral and Cancer Surgery, University of Cologne, Köln, Germany, Institute for Genomic Medicine, University of California San Diego, La Jolla, CA 92093, USA, Department of Pharmacology and Institute of Medical Informatics, National Cheng Kung University, Tainan 701, Taiwan Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan, Moores Cancer Center, University of California San Diego, La Jolla, CA 92093, USA, Institute of Basic Medical Sciences, National Cheng Kung University, Tainan 701, Taiwan, Department of Pediatrics and Rady Children's Hospital, University of California San Diego, La Jolla, CA 92093, USA, Department of General, Visceral and Cancer Surgery, University of Cologne, Köln, Germany, Institute for Genomic Medicine, University of California San Diego, La Jolla, CA 92093, USA, Department of Ph

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.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Biomarkers, Tumor / metabolism
Carcinoma, Squamous Cell / genetics*
Carcinoma, Squamous Cell / mortality
CpG Islands
DNA Methylation*
Disease Progression
Epigenesis, Genetic*
Esophageal Neoplasms / genetics*
Esophageal Neoplasms / mortality
Esophageal Squamous Cell Carcinoma
Gene Regulatory Networks*
Humans
Promoter Regions, Genetic

Substances

Biomarkers, Tumor