Abstract

DNA methylation plays a critical role in tumorigenesis through regulating oncogene activation and tumor suppressor gene silencing. Although extensively analyzed, the implication of DNA methylation in gene regulatory network is less characterized. To address this issue, in this study we performed an integrative analysis on the alteration of DNA methylation patterns and the dynamics of gene regulatory network topology across distinct stages of stomach cancer. We found the global DNA methylation patterns in different stages are generally conserved, whereas some significantly differentially methylated genes were exclusively observed in the early stage of stomach cancer. Integrative analysis of DNA methylation and network topology alteration yielded several genes which have been reported to be involved in the progression of stomach cancer, such as IGF2, ERBB2, GSTP1, MYH11, TMEM59, and SST. Finally, we demonstrated that inhibition of SST promotes cell proliferation, suggesting that DNA methylation-associated SST suppression possibly contributes to the gastric cancer progression. Taken together, our study suggests the DNA methylation-associated regulatory network analysis could be used for identifying cancer-related genes. This strategy can facilitate the understanding of gene regulatory network in cancer biology and provide a new insight into the study of DNA methylation at system level.

Highlights

  • DNA methylation plays a critical role in tumorigenesis through regulating oncogene activation and tumor suppressor gene silencing (He et al, 2008), and has raised extensive attention in the past decade

  • Due to the unavailability of DNA methylation data and the matched RNA-seq data in normal tissues, we examined the correlation between the pair of the expression level and the DNA methylation level of probes located in the promoter region of a given gene in each tumor stage

  • It has been recognized that aberrant DNA methylation play an import role in tumorigenesis

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Summary

Introduction

DNA methylation plays a critical role in tumorigenesis through regulating oncogene activation and tumor suppressor gene silencing (He et al, 2008), and has raised extensive attention in the past decade. It has been shown that tumor initiation and development are associated with aberrant DNA methylation patterns, as documented in stomach cancer development (Tahara and Arisawa, 2015; Yamamoto et al, 2016). Aberrant DNA methylation pattern is the hallmark in the cancer genome (Baylin et al, 2000; Bergman and Cedar, 2013) and is involved in malignant progression (Jones et al, 2013). Critically involved in malignancy, the implication of DNA methylation in tumorigenesis at system level is less characterized. The gene regulatory network based analysis is regarded as a powerful way to understand the mechanism of tumorigenesis at system level (Kreeger and Lauffenburger, 2010), and various robust machine learning methods based gene regulatory network inference algorithms were proposed for such analysis (Haury et al, 2012; Slawek and Arodz, 2013; Wu et al, 2016). The rapid development of deep sequencing technologies promotes the generation of a tremendous amount of sequencing data, and an increasing number of network-based methods have been recently applied to understand the molecular mechanism of tumor formation and progression (Anglani et al, 2014; Yang et al, 2014; Bicker et al, 2015)

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