Dataset Information

Identification of the Sixth Complement Component as Potential Key Genes in Hepatocellular Carcinoma via Bioinformatics Analysis.

ABSTRACT: The present study is designed to determine potential target genes involved in hepatocellular carcinoma (HCC) and provide possible underlying mechanisms of action. Several studies (GSE112790, GSE87630, and GSE56140) from the GEO database looking at molecular characteristics in HCC were screened and analyzed by GEO2R, which led to the identification of a total of 93 differentially expressed genes (DEGs). From the protein-protein interaction (PPI) network, we selected 13 key genes with high degree of variability in expression in HCC. Expression of three key genes (NQO1, CYP2C9, and C6) presented with poor overall survival (OS) in HCC patients by UALCAN. C6, which is a complement component, was found by ONCOMINE and TIMER to have low expression in many solid cancers including HCC. Besides, Kaplan-Meier plotter and UALCAN database analysis to access diseases prognosis suggested that low expression of C6 is significantly related to worse OS in LIHC patients, especially in advanced HCC patients. Finally, the TIMER analysis suggested that the C6 expression showed significant negative correlation with infiltrating levels of six immune cells. The somatic copy number alterations (SCNAs) of C6 were associated with CD4+ T cell infiltration in HCC. Taken together, these results together identified C6 as a potential key gene in the diagnosis and prognosis of HCC.

SUBMITTER: Mu D

PROVIDER: S-EPMC7556077 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identification of the Sixth Complement Component as Potential Key Genes in Hepatocellular Carcinoma via Bioinformatics Analysis.

Mu Di D Qin Feng F Li Baoshan B Zhou Qian Q

BioMed research international 20201005

The present study is designed to determine potential target genes involved in hepatocellular carcinoma (HCC) and provide possible underlying mechanisms of action. Several studies (GSE112790, GSE87630, and GSE56140) from the GEO database looking at molecular characteristics in HCC were screened and analyzed by GEO2R, which led to the identification of a total of 93 differentially expressed genes (DEGs). From the protein-protein interaction (PPI) network, we selected 13 key genes with high degree ...[more]

PMID: 33083480

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Project description:Orthotopic liver transplantation (OLT) improves the prognosis of patients with hepatocellular carcinoma (HCC). Moreover, the complement system is a powerful immune effector that can affect liver function and process of liver cirrhosis. However, studies correlating the complement system with tacrolimus metabolism after OLT are scarce. In this study, the role of single nucleotide polymorphisms (SNPs) associated with the sixth complement component (C6) in tacrolimus metabolism was investigated during the early stages of liver transplantation.The study enrolled 135 adult patients treated with OLT for HCC between August 2011 and October 2013. Ten SNPs in C6 gene and rs776746 in cytochrome P450 3A5 (CYP3A5) gene were investigated. The tacrolimus levels were monitored daily during 4 weeks after transplantation.Both donor and recipient CYP3A5 rs776746 allele A were correlated with decreased concentration/dose (C/D) ratios. Recipient C6 rs9200 allele G and donor C6 rs10052999 homozygotes were correlated with lower C/D ratios. Recipient CYP3A5 rs776746 allele A (yielded median tacrolimus C/D ratios of 225.90 at week 1 and 123.61 at week 2), C6 rs9200 allele G (exhibited median tacrolimus C/D ratios of 211.31 at week 1, 110.23 at week 2, and 99.88 at week 3), and donor CYP3A5 rs776746 allele A (exhibited median C/D ratios of 210.82 at week 1, 111.06 at week 2, 77.49 at week 3, and 85.60 at week 4) and C6 rs10052999 homozygote (exhibited median C/D ratios of 167.59 at week 2, 157.99 at week 3, and 155.36 at week 4) were associated with rapid tacrolimus metabolism. With increasing number of these alleles, patients were found to have lower tacrolimus C/D ratios at various time points during the 4 weeks after transplantation. In multiple linear regression analysis, recipient C6 rs9200 group (AA vs. GG/GA) was found to be related to tacrolimus metabolism at weeks 1, 2, and 3 (P = 0.005, P = 0.045, and P = 0.033, respectively), whereas donor C6 rs10052999 group (CC/TT vs. TC) was demonstrated to be correlated with tacrolimus metabolism only at week 4 (P = 0.001).Recipient C6 gene rs9200 polymorphism and donor C6 gene rs10052999 polymorphism are new genetic loci that affect tacrolimus metabolism in patients with HCC after OLT.

Project description:BackgroundHepatocellular carcinoma (HCC) is a type of primary liver tumor with poor prognosis and high mortality, and its molecular mechanism remains incompletely understood. This study aimed to use bioinformatics technology to identify differentially expressed genes (DEGs) in HCC pathogenesis, hoping to identify novel biomarkers or potential therapeutic targets for HCC research.MethodsThe bioinformatics analysis of our research mostly involved the following two datasets: Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). First, we screened DEGs based on the R packages (limma and edgeR). Using the DAVID database, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs were carried out. Next, the protein-protein interaction (PPI) network of the DEGs was built in the STRING database. Then, hub genes were screened through the cytoHubba plug-in, followed by verification using the GEPIA and Oncomine databases. We demonstrated differences in levels of the protein in hub genes using the Human Protein Atlas (HPA) database. Finally, the hub genes prognostic values were analyzed by the GEPIA database. Additionally, using the Comparative Toxicogenomics Database (CTD), we constructed the drug-gene interaction network.ResultsWe ended up with 763 DEGs, including 247 upregulated and 516 downregulated DEGs, that were mainly enriched in the epoxygenase P450 pathway, oxidation-reduction process, and metabolism-related pathways. Through the constructed PPI network, it can be concluded that the P53 signaling pathway and the cell cycle are the most obvious in module analysis. From the PPI, we filtered out eight hub genes, and these genes were significantly upregulated in HCC samples, findings consistent with the expression validation results. Additionally, survival analysis showed that high level gene expression of CDC20, CDK1, MAD2L1, BUB1, BUB1B, CCNB1, and CCNA2 were connected with the poor overall survival of HCC patients. Toxicogenomics analysis showed that only topotecan, oxaliplatin, and azathioprine could reduce the gene expression levels of all seven hub genes.ConclusionThe present study screened out the key genes and pathways that were related to HCC pathogenesis, which could provide new insight for the future molecularly targeted therapy and prognosis evaluation of HCC.

Dataset Information

Identification of the Sixth Complement Component as Potential Key Genes in Hepatocellular Carcinoma via Bioinformatics Analysis.

Publications

Identification of the Sixth Complement Component as Potential Key Genes in Hepatocellular Carcinoma via Bioinformatics Analysis.

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