Lun Yongzhi, Sun Jie
Department of Laboratory Medicine, School of Pharmacy and Medical Technology, Putian University, Putian 351100, Fujian Province, China.
Zhejiang Da Xue Xue Bao Yi Xue Ban. 2019 Apr 25;48(2):148-157. doi: 10.3785/j.issn.1008-9292.2019.04.05.
To identify the differentially expressed genes (DEGs) in peripheral blood mononuclear cells (PBMC) of patients with hepatocellular carcinoma (HCC) and to analyze their regulatory network.
The DEGs in PBMCs of HCC patients were screened based on GEO database. The functional enrichment analysis and interaction analysis were carried out for DEGs. MCODE algorithm was used to screen core genes of DEGs, and the mirDIP and starBase online tools were used to predict upstream miRNAs and lncRNAs of the core genes.
A total of 265 DEGs with a high credibility were identified, which were mainly enriched in the biological activity, such as regulation of cell proliferation, metabolic regulation, cell communication and signaling, and inflammatory diseases according to Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and the two analyses were correlated. Four diagnostic candidate genes were identified, including FUS RNA binding protein, C-X-C motif chemokine ligand 8, cullin 1 and RNA polymerase Ⅱ subunit H. Subsequently, 10 miRNAs, 1 lncRNAs and 38 circRNAs were predicted, and finally a lncRNA/circRNA-miRNA-mRNA-pathway regulatory networks was constructed.
The diagnostic candidate genes and its regulatory network in HCC PBMC have been identified based on data mining, which could provide potential tumor biomarkers for early diagnosis and treatment of HCC.
鉴定肝细胞癌(HCC)患者外周血单个核细胞(PBMC)中的差异表达基因(DEG),并分析其调控网络。
基于GEO数据库筛选HCC患者PBMC中的DEG。对DEG进行功能富集分析和相互作用分析。使用MCODE算法筛选DEG的核心基因,并使用mirDIP和starBase在线工具预测核心基因的上游miRNA和lncRNA。
共鉴定出265个可信度高的DEG,根据基因本体论(GO)分析和京都基因与基因组百科全书(KEGG)通路,这些基因主要富集于细胞增殖调控、代谢调控、细胞通讯和信号传导以及炎症性疾病等生物学活性,且两种分析具有相关性。鉴定出4个诊断候选基因,包括FUS RNA结合蛋白、C-X-C基序趋化因子配体8、cullin 1和RNA聚合酶Ⅱ亚基H。随后,预测了10个miRNA、1个lncRNA和38个circRNA,最终构建了lncRNA/circRNA-miRNA-mRNA-通路调控网络。
基于数据挖掘确定了HCC患者PBMC中的诊断候选基因及其调控网络,可为HCC的早期诊断和治疗提供潜在的肿瘤生物标志物。