Screening the key genes of hepatocellular adenoma via microarray analysis of DNA expression and methylation profiles

• Published in: Oncology letters 2017-10, Vol.14 (4), p.3975-3980
• Main Authors: Liu, Dan, Liu, Pengfei, Cao, Liye, Zhang, Quan, Chen, Yaqing
• Format: Article
• Language: English
• Subjects: Anemia; Bioinformatics; Biomarkers; Cell cycle; Cytochrome; Deoxyribonucleic acid; DNA; DNA methylation; Encyclopedias; Epigenetics; Gene expression; Genomes; Growth factors; Kinases; Liver cancer; Medical prognosis; Medical screening; Metabolism; Mutation; NMR; Nuclear magnetic resonance; Oncology; Ontology; Polypeptides; Tumors
• ISSN: 1792-1074; 1792-1082
• DOI: 10.3892/ol.2017.6673

The aim of the present study was to identify the biomarkers involved in the development of hepatocellular adenoma (HCA) through integrated analysis of gene expression and methylation microarray. The microarray dataset GSE7473, containing HNF1α-mutated HCA and their corresponding non-tumor livers, 5 HNF1α-mutated HCA and 4 non-related non-tumor livers, was downloaded from the Gene Expression Omnibus (GEO) database. The DNA methylation profile GSE43091, consisting of 50 HCA and 4 normal liver tissues, was also downloaded from the GEO database. Differentially expressed genes (DEGs) were identified by the limma package of . A t-test was conducted on the differentially methylated sites. Functional enrichment analysis of DEGs was performed through the Database for Annotation, Visualization and Integrated Analysis. The genes corresponding to the differentially methylated sites were obtained by the annotation files of methylation chip platform. A total of 182 DEGs and 3,902 differentially methylated sites were identified in HCA. In addition, 238 enriched GO terms, including organic acid metabolic process and carboxylic acid metabolic process, and 14 KEGG pathways, including chemical carcinogenesis, were identified. Furthermore, 12 DEGs were identified to contain differentially methylated sites, among which, 8 overlapped genes, including pregnancy zone protein and solute carrier family 22 member 1 (SLC22A1), exhibited inverse associations between gene expression levels and DNA methylation levels. The DNA methylation levels may be potential targets of HCA. The present study revealed that the 8 overlapped genes, including annexin A2, chitinase 3-like 1, fibroblast growth factor receptor 4, mal, T-cell differentiation protein like, palladin, cytoskeletal associated protein, plasmalemma vesicle associated protein and SLC22A1, may be potential therapeutic targets of HCA.