Identification of key genes and important histone modifications in hepatocellular carcinoma
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ABSTRACT:
SUBMITTER: Liu Y
PROVIDER: S-EPMC7533298 | biostudies-literature | 2020 Jan
REPOSITORIES: biostudies-literature
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Project description:Background:Alcohol-related hepatocellular carcinoma (HCC) was reported to be diagnosed at a later stage, but the mechanism was unknown. This study aimed to identify special key genes (SKGs) during alcohol-related HCC development and progression. Methods:The mRNA data of 369 HCC patients and the clinical information were downloaded from the Cancer Genome Atlas project (TCGA). The 310 patients with certain HCC-related risk factors were included for analysis and divided into seven groups according to the risk factors. Survival analyses were applied for the HCC patients of different groups. The patients with hepatitis B virus or hepatitis C virus infection only were combined into the HCC-V group for further analysis. The differentially expressed genes (DEGs) between the HCCs with alcohol consumption only (HCC-A) and HCC-V tumors were identified through limma package in R with cutoff criteria?log2 fold change (logFC)|>1.0 and p < 0.05. The DEGs between eight alcohol-related HCCs and their paired normal livers of GSE59259 from the Gene Expression Omnibus (GEO) were identified through GEO2R (a built-in tool in GEO database) with cutoff criteria |logFC|> 2.0 and adj.p < 0.05. The intersection of the two sets of DEGs was considered SKGs which were then investigated for their specificity through comparisons between HCC-A and other four HCC groups. The SKGs were analyzed for their correlations with HCC-A stage and grade and their prognostic power for HCC-A patients. The expressional differences of the SKGs in the HCCs in whole were also investigated through Gene Expression Profiling Interactive Analysis (GEPIA). The SKGs in HCC were validated through Oncomine database analysis. Results:Pathological stage is an independent prognostic factor for HCC patients. HCC-A patients were diagnosed later than HCC patients with other risk factors. Ten SKGs were identified and nine of them were confirmed for their differences in paired samples of HCC-A patients. Three (SLC22A10, CD5L, and UROC1) and four (SLC22A10, UROC1, CSAG3, and CSMD1) confirmed genes were correlated with HCC-A stage and grade, respectively. SPP2 had a lower trend in HCC-A tumors and was negatively correlated with HCC-A stage and grade. The SKGs each was differentially expressed between HCC-A and at least one of other HCC groups. CD5L was identified to be favorable prognostic factor for overall survival while CSMD1 unfavorable prognostic factor for disease-free survival for HCC-A patients and HCC patients in whole. Through Oncomine database, the dysregulations of the SKGs in HCC and their clinical significance were confirmed. Conclusion:The poor prognosis of HCC-A patients might be due to their later diagnosis. The SKGs, especially the four stage-correlated genes (CD5L, SLC22A10, UROC1, and SPP2) might play important roles in HCC development, especially alcohol-related HCC development and progression. CD5L might be useful for overall survival and CSMD1 for disease-free survival predication in HCC, especially alcohol-related HCC.
| S-EPMC6368834 | biostudies-literature
Project description:BackgroundDeregulated purine metabolism is critical for fast-growing tumor cells by providing nucleotide building blocks and cofactors. Importantly, purine antimetabolites belong to the earliest developed anticancer drugs and are still prescribed in clinics today. However, these antimetabolites can inhibit non-tumor cells and cause undesired side effects. As liver has the highest concentration of purines, it makes liver cancer a good model to study important nodes of dysregulated purine metabolism for better patient selection and precisive cancer treatment.MethodsBy using a training dataset from TCGA, we investigated the differentially expressed genes (DEG) of purine metabolism pathway (hsa00230) in hepatocellular carcinoma (HCC) and determined their clinical correlations to patient survival. A prognosis model was established by Lasso-penalized Cox regression analysis, and then validated through multiple examinations including Cox regression analysis, stratified analysis, and nomogram using another ICGC test dataset. We next treated HCC cells using chemical drugs of the key enzymes in vitro to determine targetable candidates in HCC.ResultsThe DEG analysis found 43 up-regulated and 2 down-regulated genes in the purine metabolism pathway. Among them, 10 were markedly associated with HCC patient survival. A prognostic correlation model including five genes (PPAT, DCK, ATIC, IMPDH1, RRM2) was established and then validated using the ICGC test dataset. Multivariate Cox regression analysis found that both prognostic risk model (HR = 4.703 or 3.977) and TNM stage (HR = 2.303 or 2.957) independently predicted HCC patient survival in the two datasets respectively. The up-regulations of the five genes were further validated by comparing between 10 pairs of HCC tissues and neighboring non-tumor tissues. In vitro cellular experiments further confirmed that inhibition of IMPDH1 significantly repressed HCC cell proliferation.ConclusionIn summary, this study suggests that purine metabolism is deregulated in HCC. The prognostic gene correlation model based on the five purine metabolic genes may be useful in predicting HCC prognosis and patient selection. Moreover, the deregulated genes are targetable by specific inhibitors.
| S-EPMC7841304 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) is one of the most common malignant neoplasms worldwide, however the underlying mechanisms and gene signatures of HCC are unknown. In the present study the profile datasets of four cohorts were integrated to elucidate the pathways and candidate genes of HCC. The expression profiles GSE25097, GSE45267, GSE57957 and GSE62232 were downloaded from the Gene Expression Omnibus database, including 436 HCC and 94 normal liver tissues. A total of 185 differentially expressed genes (DEGs) were identified in HCC, including 92 upregulated genes and 92 downregulated genes. Gene ontology (GO) was performed, which revealed that the upregulated DEGs were primarily enriched in cell division, mitotic nuclear division, mitotic cytokinesis and G1/S transition of the mitotic cell cycle. Pathway enrichment was analyzed based on the Kyoto Encyclopedia of Genes and Genomes database to assess the functional relevance of DEGs. The most significant module was selected from protein-protein interactions and 15 important hub genes were identified. The sub-networks of hub genes were involved in cell division, p53 signaling, and T lymphotropic virus type I infection signaling pathways. In conclusion, the present study revealed that the identified DEG candidate genes may promote the understanding of the cause and molecular mechanisms underlying the development of HCC and that these candidates and signal pathways may be potential targets of clinical therapy for HCC.
| S-EPMC5958738 | biostudies-literature
Project description:Emerging evidence indicates that various functional genes with altered expression are involved in the tumor progression of human cancers. This study is aimed at identifying novel key genes that may be used for hepatocellular carcinoma (HCC) diagnosis, prognosis, and targeted therapy. This study included 3 expression profiles (GSE45267, GSE74656, and GSE84402), which were obtained from the Gene Expression Omnibus (GEO). GEO2R was used to analyze the differentially expressed genes (DEGs) between HCC and normal samples. The functional and pathway enrichment analysis was performed by the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network of the identified DEGs was constructed using the Search Tool for the Retrieval of Interacting Gene, and hub genes were identified. ONCOMINE and CCLE databases were used to verify the expression of the hub genes in HCC tissues and cells. Kaplan-Meier plotter was used to assess the effects of the hub genes on the overall survival of HCC patients. A total of 99 DEGs were identified from the 3 expression profiles. These DEGs were enriched with functional processes and pathways related to HCC pathogenesis. From the PPI network, 5 hub genes were identified. The expression of the 5 hub genes was all upregulated in HCC tissues and cells compared with the control tissues and cells. Kaplan-Meier survival curves indicated that high expression of cyclin-dependent kinase (CDK1), cyclin B1 (CCNB1), cyclin B2 (CCNB2), MAD2 mitotic arrest deficient-like 1 (MAD2L1), and topoisomerase II? (TOP2A) predicted poor overall survival in HCC patients (all log-rank P < 0.01). These results revealed that the DEGs may serve as candidate key genes during HCC pathogenesis. The 5 hub genes, including CDK1, CCNB1, CCNB2, MAD2L1, and TOP2A, may serve as promising prognostic biomarkers in HCC.
| S-EPMC6893264 | biostudies-literature
Project description:Background:Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths worldwide. Although multiple efforts have been made to understand the development of HCC, morbidity, and mortality rates remain high. In this study, we aimed to discover the mRNAs and long non-coding RNAs (lncRNAs) that contribute to the progression of HCC. We constructed a lncRNA-related competitive endogenous RNA (ceRNA) network to elucidate the molecular regulatory mechanism underlying HCC. Methods:A microarray dataset (GSE54238) containing information about both mRNAs and lncRNAs was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and lncRNAs (DElncRNAs) in tumor tissues and non-cancerous tissues were identified using the limma package of the R software. The miRNAs that are targeted by DElncRNAs were predicted using miRcode, while the target mRNAs of miRNAs were retrieved from miRDB, miRTarBas, and TargetScan. Functional annotation and pathway enrichment of DEGs were performed using the EnrichNet website. We constructed a protein-protein interaction (PPI) network of DEGs using STRING, and identified the hub genes using Cytoscape. Survival analysis of the hub genes and DElncRNAs was performed using the gene expression profiling interactive analysis database. The expression of molecules with prognostic values was validated on the UALCAN database. The hepatic expression of hub genes was examined using the Human Protein Atlas. The hub genes and DElncRNAs with prognostic values as well as the predictive miRNAs were selected to construct the ceRNA networks. Results:We found that 10 hub genes (KPNA2, MCM7, CKS2, KIF23, HMGB2, ZWINT, E2F1, MCM4, H2AFX, and EZH2) and four lncRNAs (FAM182B, SNHG6, SNHG1, and SNHG3) with prognostic values were overexpressed in the hepatic tumor samples. We also constructed a network containing 10 lncRNA-miRNA-mRNA pathways, which might be responsible for regulating the biological mechanisms underlying HCC. Conclusion:We found that the 10 significantly overexpressed hub genes and four lncRNAs were negatively correlated with the prognosis of HCC. Further, we suggest that lncRNA SNHG1 and the SNHG3-related ceRNAs can be potential research targets for exploring the molecular mechanisms of HCC.
| S-EPMC6827457 | biostudies-literature
Project description:BackgroundHepatocellular carcinoma (HCC) is the most common liver malignancy worldwide. However, present studies of its multiple gene interaction and cellular pathways still could not explain the initiation and development of HCC perfectly. To find the key genes and miRNAs as well as their potential molecular mechanisms in HCC, microarray data GSE22058, GSE25097, and GSE57958 were analyzed.MethodsThe microarray datasets GSE22058, GSE25097, and GSE57958, including mRNA and miRNA profiles, were downloaded from the GEO database and were analyzed using GEO2R. Functional and pathway enrichment analyses were performed using the DAVID database, and the protein-protein interaction (PPI) network was constructed using the Cytoscape software. Finally, miRDB was applied to predict the targets of the differentially expressed miRNAs (DEMs).ResultsA total of 115 differentially expressed genes (DEGs) were found in HCC, including 52 up-regulated genes and 63 down-regulated genes. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses from DAVID showed that up-regulated genes were significantly enriched in chromosome segregation and cell division, while the down-regulated genes were mainly involved in complement activation, protein activation cascades, carboxylic acid metabolic processes, oxoacid metabolic processes, and the immune response. From the PPI network, the 18 nodes with the highest degree were screened as hub genes. Among them, ESR1 was found to have close interactions with FOXO1, CXCL12, and GNAO1. In addition, a total of 64 DEMs were identified, which included 58 up-regulated miRNAs and 6 down-regulated miRNAs. ESR1 was potentially targeted by five miRNAs, including hsa-mir-18a and hsa-mir-221.ConclusionsThe roles of DEMs like hsa-mir-221 in HCC through interactions with DEGs such as ESR1 and CXCL12 may provide new clues for the diagnosis and treatment of HCC patients.
| S-EPMC5356276 | biostudies-literature
Project description:Histone modifications and their modifying enzymes are fundamentally involved in the epigenetic regulation of adipogenesis. This study aimed to define the roles of various histone modifications and their "division of labor" in fat cell differentiation. To achieve these goals, we examined the distribution patterns of eight core histone modifications at five key adipogenic regulatory genes, Pref-1, C/EBPβ, C/EBPα, PPARγ2 and aP2, during the adipogenesis of C3H 10T1/2 mouse mesenchymal stem cells (MSCs) and 3T3-L1 preadipocytes. We found that the examined histone modifications are globally stable throughout adipogenesis but show distinct and highly dynamic distribution patterns at specific genes. For example, the Pref-1 gene has lower levels of active chromatin markers and significantly higher H3 K27 tri-methylation in MSCs compared with committed preadipocytes; the C/EBPβ gene is enriched in active chromatin markers at its 3'-UTR; the C/EBPα gene is predominantly marked by H3 K27 tri-methylation in adipogenic precursor cells, and this repressive marker decreases dramatically upon induction; the PPARγ2 and aP2 genes show increased histone acetylation on both H3 and H4 tails during adipogenesis. Further functional studies revealed that the decreased level of H3 K27 tri-methylation leads to de-repression of Pref-1 gene, while the increased level of histone acetylation activates the transcription of PPARγ2 and aP2 genes. Moreover, the active histone modification-marked 3'-UTR of C/EBPβ gene was demonstrated as a strong enhancer element by luciferase assay. Our results indicate that histone modifications are gene-specific at adipogenic regulator genes, and they play distinct roles in regulating the transcriptional network during adipogenesis.
| S-EPMC3552913 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) is the most commonly diagnosed malignancy of the liver. A more thorough understanding of HCC pathogenesis will provide novel targets for development of cancer drugs to effectively treat HCC. To further this goal, we carried out a proteomic profiling of HCC cell lines Huh-7.4 and Huh-7.5. These two cell lines were derived from subgenomic HCV RNA-replicating Huh-7 cells upon clearance of HCV RNA by antiviral drug treatment. Initially, the tumorigenicity of each cell line was determined and compared in parallel in the same immunedeficient mice. Strikingly, the Huh-7.4 cell line was able to induce tumors, whereas the Huh-7.5 cell line failed to do so, providing unique model systems for identifying cellular genes and pathways important for HCC development and progression. Subsequently, one-dimensional LC-MS/MS proteomic and bioinformatics analyses were performed in the hope of identifying unique cellular genes and pathways responsible for HCC tumorigenicity. Interestingly, a total of 130 cellular genes were found to be significantly up- or downregulated between these two cell lines (r>3 fold, P<0.001). Also, EIF (EIF2&4), mTOR/p70S6K, ERK5, and EGFR signaling pathways were significantly different. Overall, these results provide significant new information to shed light on the underlying biological processes involved in HCC development and progression.
| S-EPMC5707090 | biostudies-literature
Project description: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.
| S-EPMC7556077 | biostudies-literature
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.
| S-EPMC7985067 | biostudies-literature