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

التفاصيل البيبلوغرافية
العنوان: Using Integrated Bioinformatics Analysis to Identify Abnormally Methylated Differentially Expressed Genes in Hepatocellular Carcinoma
المؤلفون: Qing-Lian Chen, Chong Zhong, Kun-Liang Feng, Ya Li, Qian Yan, Chun-Feng Xie, Ji-Nan Wang, Li-Hua Liu, Chong-Kai Fang
المصدر: International Journal of General Medicine
بيانات النشر: Informa UK Limited, 2021.
سنة النشر: 2021
مصطلحات موضوعية: bioinformatics analysis, Microarray, business.industry, hub genes, International Journal of General Medicine, hepatocellular carcinoma, General Medicine, Computational biology, Methylation, 030204 cardiovascular system & hematology, medicine.disease_cause, Gene expression profiling, 03 medical and health sciences, 0302 clinical medicine, 030220 oncology & carcinogenesis, Gene expression, gene expression, Medicine, methylation, Signal transduction, business, Carcinogenesis, Gene, Estrogen receptor alpha, Original Research
الوصف: Qing-Lian Chen,1,2,* Qian Yan,1,* Kun-Liang Feng,1,2,* Chun-Feng Xie,1,2,* Chong-Kai Fang,1,2 Ji-Nan Wang,1,2 Li-Hua Liu,2,3 Ya Li,3 Chong Zhong2,3 1Guangzhou University of Chinese Medicine, Guangzhou, 510405, People’s Republic of China; 2Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510405, People’s Republic of China; 3Lingnan Medical Research Center, Guangzhou University of Chinese Medicine, Guangzhou, 510405, People’s Republic of China*These authors contributed equally to this workCorrespondence: Chong ZhongDepartment of Hepatobiliary Surgery, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, 16 Airport Road, Guangzhou, 510405, People’s Republic of ChinaTel +86-20-36596301Email zhongchong1732@gzucm.edu.cnObjective: 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.Keywords: methylation, hepatocellular carcinoma, hub genes, gene expression, bioinformatics analysis
وصف الملف: text/html
تدمد: 1178-7074
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9fa20ded721bd73315ad21f0ada54589Test
https://doi.org/10.2147/ijgm.s294505Test
حقوق: OPEN
رقم الانضمام: edsair.doi.dedup.....9fa20ded721bd73315ad21f0ada54589
قاعدة البيانات: OpenAIRE