Bioinformatics analysis of hepatitis C virus genotype 2a-induced human hepatocellular carcinoma in Huh7 cells

Abstract

Hepatocellular carcinoma (HCC) is a liver cancer that could be induced by hepatitis C virus genotype 2a Japanese fulminant hepatitis-1 (JFH-1) strain. The aim of this study was to investigate the molecular mechanisms of HCC. The microarray data GSE20948 includes 14 JFH-1- and 14 mock (equal volume of medium [control])-infected Huh7 samples. The data were downloaded from the Gene Expression Omnibus. After data processing, soft cluster analyses were performed to identify co-regulated genes with similar temporal expression patterns. Functional and pathway enrichment analyses, as well as functional annotation analysis, were performed. Subsequently, combined networks of protein–protein interaction network, microRNA regulatory network, and transcriptional regulatory network were constructed. Hub nodes, modules, and five clusters of co-regulated genes were also identified. In total, 173 up and 207 down co-regulated genes were separately identified in JFH-1-infected Huh7 cells compared with those of control cells. Functional enrichment analysis indicated that up co-regulated genes were related to skeletal system morphogenesis and neuron differentiation and down co-regulated genes were related to steroid/cholesterol/sterol metabolisms. Hub genes (such as IRF1, GBP1, ICAM1, Foxa1, DHCR7, HMGCS2, and MSMO1) were identified. Transcription factors IRF1 and Foxa1 were the targets of miR-130a, miR-17-5p, and miR-20a. PPARGC1A was targeted by miR-29 family, and MSMO1 was the target of miR-23 family. Hub nodes (such as IRF1, GBP1, ICAM1, Foxa1, DHCR7, HMGCS2, and MSMO1) and microRNAs might be used as candidate biomarkers of JFH-1-infected HCC.

Feedback Loop Regulation of SCAP/SREBP-1 by miR-29 Modulates EGFR Signaling-Driven Glioblastoma Growth

“…Since miR-29 has been reported to be involved in lipid metabolism (Kurtz et al, 2015; Kurtz et al, 2014; Xu et al, 2016), we performed a correlation analysis between SREBF1 expression and miR-29 levels based on genomic EGFR status in a large cohort of GBM patient samples (TCGA database) (Cerami et al, 2012; Gao et al, 2013). Interestingly, in GBM patients with altered EGFR (amplification and/or mutation), the data show that expression of the 3 members of the miR-29 family, miR-29a, -29b and -29c (Zhang et al, 2012), positively correlated with the expression of SREBF1 (Figures 1A and S1A).…”

“…In particular, miR-29 has been shown to suppress GBM cell growth in vitro when transfected (Xu et al, 2015) and to connect with lipid metabolism pathways in liver and hepatoma cells (Kurtz et al, 2014; Xu et al, 2016). Thus, we asked the question whether miR-29 is involved in the EGFR signaling-regulated SCAP/SREBP-1 pathway and GBM tumor growth.…”

Prognostic value of lipid metabolism‐related genes in head and neck squamous cell carcinoma

“…It is reported that CYP27B1, CYP2D6, and TRIB3 are directly or indirectly involved in HNSCC development and progression 36–39 . DGKG, DHCR7, LPIN1, PIP5K1B, PLA2G2D, and RDH16 are involved in the development of other tumors 26,28,40–43 . However, ARSI and PHYH have not been previously studied in cancers.…”

Biological Networks for Cancer Candidate Biomarkers Discovery

“… 82 An SDLS method was used to construct a network that combined gene expression and copy number alteration data to describe the interconnections between genes. 14 Xu et al 83 constructed a combinatorial network by integrating PPI networks, microRNA regulatory networks, and GRNs and took the network hubs as candidate biomarkers for hepatocellular carcinoma. High-throughput screening for drug sensitivity patterns are also frequently integrated into biomarker discovery, such as the drug–drug network that was employed in a systemic identification of genomic markers of drug sensitivity.…”