Using Integrated Bioinformatics Analysis to Identify Abnormally Methylated Differentially Expressed Genes in Hepatocellular Carcinoma

Abstract

Objective For the identification of abnormally methylated differentially expressed genes (MDEGs) in hepatocellular carcinoma (HCC), this study integrated four microarray datasets to investigate the fundamental mechanisms of tumorigenesis. Methods We obtained the expression (GSE76427, GSE57957) and methylation (GSE89852, GSE54503) profiles from Gene Expression Omnibus (GEO). The abnormally MDEGs were identified by using R software. We used the clusterProfiler package for the functional and pathway enrichment analysis. The String database was used to build the protein–protein interaction (PPI) network and visualize it in Cytoscape. MCODE was employed in the module analysis. Additionally, Gene Expression Profiling Interactive Analysis (GEPIA) and The Cancer Genome Atlas (TCGA) were employed to validate results. Lastly, we used cBioPortal software to examine the hub genetic alterations. Results We identified 162 hypermethylated, down-regulated genes and 190 hypomethylated, up-regulated genes. Up-regulated genes with low methylation were enriched in biological processes, such as keratinocyte proliferation, and calcium homeostasis. Pathway analysis was enriched in the AMPK and PI3K-Akt signaling pathways. The PPI network identified PTK2, VWF, and ITGA2 as hypomethylated, high-expressing hub genes. Down-regulated genes with high methylation were related to responses to peptide hormones and estradiol, multi-multicellular organism process. Pathway analysis indicated enrichment in camp, oxytocin signaling pathways. The PPI network identified CFTR, ESR1, and CXCL12 as hypermethylated, low-expressing hub genes. Upon verification in TCGA databases, we found that the expression and methylation statuses of the hub genes changed significantly, and it was consistent with our results. Conclusion The novel abnormally MDEGs and pathways in HCC were identified. These results helped us further understand the molecular mechanisms underlying HCC invasion, metastasis, and development. Hub genes can serve as biomarkers for an accurate diagnosis and treatment of HCC, and PTK2, VWF, ITGA2, CFTR, ESR1, and CXCL12 are included.

Pan-carcinogenic analysis of ITGA2 in human tumor carcinogenesis

“…Therefore, the study of DNA methylation is of great signi cance for the further understanding of gene expression, ontogeny and the mechanism of the occurrence and development of diseases. Our rst study of ITGA2 methylation in tumors found that ITGA2 methylation levels were lower in cholangiocarcinoma, lung adenocarcinoma, hepatocellular carcinoma, colon cancer, and gastric cancer than in normal tissues, this is consistent with previous studies [10,[26][27]. At the same time, previous studies have shown that ITGA2 methylation levels are lower in acute myeloid leukemia, breast cancer, and thyroid cancer tumors [25,28,29].…”

Identification and validation of core genes as promising diagnostic signature in hepatocellular carcinoma based on integrated bioinformatics approach

“…In addition, for protein expression in the human protein atlas, a web interface ( http://www.proteinatlas.org ) has been utilized to assess the role of genes in normal as well as HCC samples. Subsequently, another interface, UALCAN( http://ualcan.path.uab.edu/ ), was used for the examination of relationships between different stages of cancer for mRNA expression of the genes of interest using the TCGA set of data 43 .…”

“…uab. edu/), was used for the examination of relationships between different stages of cancer for mRNA expression of the genes of interest using the TCGA set of data 43 .…”

Identification of Differentially Expressed Genes Associated with the Prognosis and Diagnosis of Hepatocellular Carcinoma by Integrated Bioinformatics Analysis

“…The methylation role in gene expression was identified from 162 hypermethylated genes (downregulated) and 190 hypomethylated genes (upregulated). In biological processes, such as keratinocyte growth and calcium homeostasis, overregulated genes with poor methylation were identified [ 38 ]. PTK2, ITGA2, and VWF were found as highly expressing hypomethylated hub genes detected in the PPI network [ 38 ].…”

“…In biological processes, such as keratinocyte growth and calcium homeostasis, overregulated genes with poor methylation were identified [ 38 ]. PTK2, ITGA2, and VWF were found as highly expressing hypomethylated hub genes detected in the PPI network [ 38 ]. Three gene methylation levels, KPNA2, MCM3, and LRRC1, were linked to HCC clinical characteristics [ 39 ].…”