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Comprehensive Analysis of DNA Methylation and Gene Expression Profles in Cholangiocarcinoma Cheng Zhang1, Bingye Zhang1, Di Meng2 and Chunlin Ge1*

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Comprehensive Analysis of DNA Methylation and Gene Expression Profles in Cholangiocarcinoma Cheng Zhang1, Bingye Zhang1, Di Meng2 and Chunlin Ge1* Zhang et al. Cancer Cell Int (2019) 19:352 https://doi.org/10.1186/s12935-019-1080-y Cancer Cell International PRIMARY RESEARCH Open Access Comprehensive analysis of DNA methylation and gene expression profles in cholangiocarcinoma Cheng Zhang1, Bingye Zhang1, Di Meng2 and Chunlin Ge1* Abstract Background: The incidence of cholangiocarcinoma (CCA) has risen in recent years, and it has become a signifcant health burden worldwide. However, the mechanisms underlying tumorigenesis and progression of this disease remain largely unknown. An increasing number of studies have demonstrated crucial biological functions of epige- netic modifcations, especially DNA methylation, in CCA. The present study aimed to identify and analyze methylation- regulated diferentially expressed genes (MeDEGs) involved in CCA tumorigenesis and progression by bioinformatics analysis. Methods: The gene expression profling dataset (GSE119336) and gene methylation profling dataset (GSE38860) were obtained from the Gene Expression Omnibus (GEO) database. Diferentially expressed genes (DEGs) and diferentially methylated genes (DMGs) were identifed using the limma packages of R and GEO2R, respectively. The MeDEGs were obtained by overlapping the DEGs and DMGs. Functional enrichment analyses of these genes were then carried out. Protein–protein interaction (PPI) networks were constructed using STRING and visualized in Cytoscape to determine hub genes. Finally, the results were verifed based on The Cancer Genome Atlas (TCGA) database. Results: We identifed 98 hypermethylated, downregulated genes and 93 hypomethylated, upregulated genes after overlapping the DEGs and DMGs. These genes were mainly enriched in the biological processes of the cell cycle, nuclear division, xenobiotic metabolism, drug catabolism, and negative regulation of proteolysis. The top nine hub genes of the PPI network were F2, AHSG, RRM2, AURKB, CCNA2, TOP2A, BIRC5, PLK1, and ASPM. Moreover, the expres- sion and methylation status of the hub genes were signifcantly altered in TCGA. Conclusions: Our study identifed novel methylation-regulated diferentially expressed genes (MeDEGs) and explored their related pathways and functions in CCA, which may provide novel insights into a further understanding of methylation-mediated regulatory mechanisms in CCA. Keywords: Cholangiocarcinoma, Methylation, Bioinformatics Background Cholangiocarcinoma (CCA) is a fatal malignancy origi- nating from the epithelial cells of the biliary tree [1]. According to its anatomical location, the most contem- *Correspondence: [email protected] porary classifcation of CCA includes intrahepatic, peri- 1 Department of Pancreatic and Biliary Surgery, The First Hospital of China hilar, and distal subtypes [2]. Surgical resection remains Medical University, Shenyang 110001, Liaoning, China the only potentially curative treatment for all subtypes Full list of author information is available at the end of the article [1]. Unfortunately, early diagnosis is rare due to a lack of © The Author(s) 2019. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://crea- tivecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdo- main/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Zhang et al. Cancer Cell Int (2019) 19:352 Page 2 of 13 specifc clinical symptoms [3]. Only about one-third of profling or whole-genome sequencing that contributed CCA patients are eligible for surgery; most patients are to cholangiocarcinogenesis and might serve as meth- often diagnosed with unresectable or metastatic disease ylation biomarkers in CCA [18, 19]. However, separate [4]. Even so, the recurrence and progression to distant DEG and DMG analysis from a single study are limited, metastasis are common within 2 years of resection [5]. and multiple overlapping available datasets may provide Overall survival for patients with unresectable CCA does more accurate and reliable clues through comprehensive not exceed 14 months, even with systemic chemotherapy bioinformatics analysis [20]. Tus far, there is still a lack [6]. In addition, the incidence of CCA seems to be on the of conjoint analysis involving both gene expression and rise, especially for intrahepatic tumors [6]. Terefore, methylation profling microarray datasets in CCA. cumulative cholangiocarcinoma mortality rates have In the present study, we performed an integrated bio- also increased by 39% [2]. Tus, exploring the molecular informatics analysis based on gene expression profl- mechanisms underlying the pathogenesis and develop- ing by high-throughput sequencing (GSE119336) and ment of CCA is urgently needed. gene methylation profling microarray (GSE38860). Te DNA methylation is a central epigenetic modifcation methylation-regulated diferentially expressed genes that plays a key role in cellular processes, such as genome (MeDEGs) were identifed and then subjected to enrich- regulation, organism development, and disease [7]. ment analysis. Moreover, we constructed a protein–pro- Importantly, the dysregulation of DNA methylation pat- tein interaction (PPI) network to identify hub genes to terns has been increasingly recognized as an important screen novel biomarkers and therapeutic targets in CCA cellular event during both the initiation and late stages for future research. of oncogenesis [8, 9]. To date, numerous studies have demonstrated a crucial role for both hypermethylation Methods of tumor suppressor genes and global hypomethylation RNA‑Seq and microarray data of oncogenes in cancer development and progression, We obtained the gene expression profling dataset gener- including in CCA [8, 10]. For instance, Chen et al. [11] ated by high-throughput sequencing (GSE119336) and found that the O6-methylguanine-DNA methyltrans- the microarray-based gene methylation profling dataset ferase (MGMT) promoter was highly methylated, and (GSE38860) from the publicly available Gene Expression the expression level of MGMT was positively corre- Omnibus database (GEO, https ://www.ncbi.nlm.nih.gov/ lated with overall survival rates and histological grade in geo/). Te expression dataset (GSE119336) contained 15 CCA. In addition, the aberrant methylation of GATA-5, pairs of CCA tumors and matched non-tumor tissues, ANGPTL4, and DLEC1 has been shown to participate which was based on the GPL11154 platform (Illumina in the initiation and progression of this disease [12–14]. HiSeq 2000). Te DNA methylation dataset (GSE38860), Despite the identifcation of several individual genes with which was generated on the GPL8490 platform (Illumina specifc hypomethylation or hypermethylation in CCA, HumanMethylation27 BeadChip), included a total of 28 comprehensive network studies based on methylation primary CCA tissues and six matched adjacent normal profles and related pathways for these genes have been tissues. largely inadequate. Over the past decade, gene profling and next-gen- Identifcation of MeDEGs eration sequencing technology have emerged as indis- GEO2R (http://www.ncbi.nlm.nih.gov/geo/geo2r /) is pensable tools for cancer studies because they allow an online analysis tool that allows users to compare two the detection of cancer-related genetic and epigenetic or more groups of samples in a GEO Series to identify alterations, such as mutations, copy number variations, deregulated genes under specifc experimental condi- and DNA methylation changes across more extensive tions. In this study, GEO2R was adopted to screen for dif- genomic regions [15, 16]. Te bioinformatics analysis ferentially methylated genes (DMGs). |t| > 2 and P < 0.05 of these data can provide valuable information for CCA were considered statistically signifcant. In addition, research. For example, Kong et al. identifed three dif- diferentially expressed genes (DEGs) were identifed ferentially expressed genes (DEGs), UCA1, miR-122, using the limma R package with a threshold of |log- and CLIC1, based on next-generation sequencing data in 2FoldChange| > 2 and P < 0.05. Using the lookup func- CCA [17]. Analysis of these dysregulated genes showed tion (VLOOKUP) of excel, we overlapped the GSE38860 that they could promote CCA progression through and GSE119336 datasets. Finally, hypomethylation-high the regulation of miR-122/CLIC1 and activation of the expression genes were obtained after superimposition ERK/MAPK signaling pathway [17]. Furthermore, both of upregulated and hypomethylated genes, and hyper- Farshidfar et al. and Jusakul et al. identifed many dif- methylation-low expression genes were obtained after ferentially methylated genes (DMGs) by methylation superimposition of downregulated and hypermethylated Zhang et al. Cancer Cell Int (2019) 19:352 Page 3 of 13 genes. Te hypomethylation-high
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