High-throughput sequencing-based analysis of gene expression of hepatitis B virus infection-associated human hepatocellular carcinoma.
ABSTRACT: Hepatitis B virus (HBV) infection is a critical factor for the initiation and progression of hepatocellular carcinoma (HCC). Gene expression profiles for HBV-associated HCC may provide valuable insight for the diagnosis and treatment of this type of HCC. The present study aimed to screen the differential genes in human HCC tissues based on high-throughput sequencing and to predict the potential therapeutic targets. Total mRNA was extracted from human HCC tissues and paracancerous tissues and sequenced using the Hiseq4000 sequencing platform. Differential gene expressions were screened and further analyzed using quantitative PCR and immunohistochemistry. A total of 2,386 differentially expressed genes were screened. Of these, 1119 were upregulated and 1,267 were downregulated in paracancerous tissues compared with tumor tissues. Gene Ontology term analysis demonstrated that differentially expressed genes were involved in carboxylic acid catabolism, monocarboxylic acid metabolic processes and ?-amino acid metabolic processes. Molecular functional analysis revealed that the differentially expressed genes functioned in oxidoreductase activity, for example acting on CH-OH group of donors and permitting identical protein binding, anion binding, coenzyme binding and monocarxylic acid transporter activity. The Kyoto Encyclopedia of Genes and Genomes analysis reported that the differentially expressed genes were primarily concentrated in 20 signaling pathways, such as valine, leucine and leucine degradation, retinol metabolism and the cell cycle. Differential expression of proteins regulating the cell cycle, including stratifin, cyclin B1 and cyclin-dependent kinase 1, were significantly higher in tumor tissue compared with those in paracancerous tissue at both the mRNA and protein levels. These results were consistent with those obtained from high-throughput sequencing, indicating the reliability of the high-throughput sequencing. Together, these results identified differentially expressed genes and predicted the subsequent signaling pathways, which may be involved in the occurrence and development of HCC. Therefore, the present study may provide novel implications in the therapeutic and diagnosis of HCC.
Project description:Hepatitis B virus (HBV) affects the malignant phenotype of hepatocellular carcinoma (HCC). The aim of the present study was to investigate the integration sites of HBV DNA and the expression of the zinc finger protein, zinc finger and BTB domain containing 20 (ZBTB20) in patients with hepatocellular carcinoma. Integration of the HBV gene was detected using a high?throughput sequencing technique based on the HBV?Alu?PCR method. The expression of ZBTB20 was detected by western blotting. HBVX integration sites were detected in ~70% of the HCC tissue samples. HBV?integrated subgene X detection suggested that 67% of the integrated specimens were inserted into the host X gene in a forward direction, 57% in a reverse direction, 24% in both forward and reverse directions, and 38% had two HBV integration sites. A total of 3,320 HBV integration sites were identified, including 1,397 in HCC tissues, 1,205 in paracancerous tissues and 718 in normal liver tissues. HBV integration fragments displayed enrichment in the 200?800 bp region. Additionally, the results suggested that HBV was highly integrated into transmembrane phosphatase with tensin homology, long intergenic non?protein coding RNA (LINC)00618, LOC101929241, ACTR3 pseudogene 5, LINC00999, LOC101928775, deleted in oesophageal cancer 1, LINC00824, EBF transcription factor 2 and ZBTB20 in tumour tissues. Furthermore, the expression of ZBTB20 was upregulated in HCC tissues compared with normal control liver tissues, and was associated with HBV integration frequency. The present study suggested that HBV DNA integrated into upregulated ZBTB20 in patients with hepatocellular carcinoma, which might promote the occurrence and development of HCC. Furthermore, the results of the present study may provide a theoretical basis for the diagnosis and treatment of HCC.
Project description:Background:The current study aims at using the whole genome expression profile chips for systematically investigating the diagnostic and prognostic values of excision repair cross-complementation (ERCC) genes in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). Materials and methods:Whole genome expression profile chips were obtained from the GSE14520. The receiver-operating characteristic (ROC) curve, survival analysis, and nomogram were used to investigate the diagnostic and prognostic values of ERCC genes. Investigation of the potential function of ERCC8 was carried out by gene set enrichment analysis (GSEA) and genome-wide coexpression analysis. Results:ROC analysis suggests that six ERCC genes (ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, and ERCC8) were dysregulated and may have potential to distinguish between HBV-related HCC tumor and paracancerous tissues (area under the curve of ROC ranged from 0.623 to 0.744). Survival analysis demonstrated that high ERCC8 expression was associated with a significantly decreased risk of recurrence (adjusted P=0.021; HR=0.643; 95% CI=0.442-0.937) and death (adjusted P=0.049; HR=0.631; 95% CI=0.399-0.998) in HBV-related HCC. Then, we also developed two nomograms for the HBV-related HCC individualized prognosis predictions. GSEA suggests that the high expression of ERCC8 may have involvement in the energy metabolism biological processes. As the genome-wide coexpression analysis and functional assessment of ERCC8 suggest, those coexpressed genes were significantly enriched in multiple biological processes of DNA damage and repair. Conclusion:The present study indicates that six ERCC genes (ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, and ERCC8) were dysregulated between HBV-related HCC tumor and paracancerous tissues and that the mRNA expression of ERCC8 may serve as a potential biomarker for the HBV-related HCC prognosis.
Project description:Purpose:This study was conducted to investigate the differentially expressed profiles of long non-coding RNAs (lncRNAs) in HBV-associated HCC (HBV-HCC), which may serve as potential diagnostic biomarkers and therapeutic targets. Methods:To examine the differentially expressed profiles of lncRNAs and mRNAs using microarray analysis, we collected 15 specimens: five HBV-associated HCC tissues, five paired adjacent peritumoral liver tissues (APLT), and five distant peritumoral liver tissues (DPLT). Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to predict the biological roles and potential signaling pathways of these dysregulated mRNAs. In addition, lncRNA-mRNA co-expression network and signal transduction pathway network (Signal-net) were employed to further explore the potential target genes and roles of dysregulated lncRNAs in HBV-HCC pathogenesis. Finally, quantitative real-time PCR (qRT-PCR) was used to confirm the expression of six selected dysregulated lncRNAs. Results:A total number of 719 lncRNAs and 3438 mRNAs were significantly more dysregulated in HBV-HCC tissues than in APLT and DPLT (fold change > 2, P < 0.05, FDR < 0.05). Additionally, 337 GO terms and 53 KEGG pathways were established to be significantly enriched. These dysregulated mRNAs were mainly enriched in metabolism-related biological processes. Additionally, lncRNA-mRNA coexpression network analysis showed that NONHSAT053785 is at the core of the network. Furthermore, the Signal-net analysis showed that CYP3A4 was gene with the highest degree. Finally, the data of five of the six selected differentially expressed lncRNAs were in agreement with the microarray data obtained by qRT-PCR verification. Conclusion:Our study revealed the differentially expressed profiles of lncRNAs and mRNAs for HBV-HCC, and five novel dysregulated lncRNAs were identified in HBV-HCC tissues. The aforementioned dysregulated lncRNAs may represent potential diagnostic biomarkers and therapeutic targets of HBV-HCC, which needs to be validated in future studies.
Project description:Hepatocellular carcinoma (HCC) is one of the most lethal cancers globally. Hepatitis B virus (HBV) infection might cause chronic hepatitis and cirrhosis, leading to HCC. To screen prognostic genes and therapeutic targets for HCC by bioinformatics analysis and determine the mechanisms underlying HBV-related HCC, three high-throughput RNA-seq based raw datasets, namely GSE25599, GSE77509, and GSE94660, were obtained from the Gene Expression Omnibus database, and one RNA-seq raw dataset was acquired from The Cancer Genome Atlas (TCGA). Overall, 103 genes were up-regulated and 127 were down-regulated. A protein-protein interaction (PPI) network was established using Cytoscape software, and 12 pivotal genes were selected as hub genes. The 230 differentially expressed genes and 12 hub genes were subjected to functional and pathway enrichment analyses, and the results suggested that cell cycle, nuclear division, mitotic nuclear division, oocyte meiosis, retinol metabolism, and p53 signaling-related pathways play important roles in HBV-related HCC progression. Further, among the 12 hub genes, kinesin family member 11 (KIF11), TPX2 microtubule nucleation factor (TPX2), kinesin family member 20A (KIF20A), and cyclin B2 (CCNB2) were identified as independent prognostic genes by survival analysis and univariate and multivariate Cox regression analysis. These four genes showed higher expression levels in HCC than in normal tissue samples, as identified upon analyses with Oncomine. In addition, in comparison with normal tissues, the expression levels of KIF11, TPX2, KIF20A, and CCNB2 were higher in HBV-related HCC than in HCV-related HCC tissues. In conclusion, our results suggest that KIF11, TPX2, KIF20A, and CCNB2 might be involved in the carcinogenesis and development of HBV-related HCC. They can thus be used as independent prognostic genes and novel biomarkers for the diagnosis of HBV-related HCC and development of pertinent therapeutic strategies.
Project description:RNA-seq is a powerful tool for comprehensive characterization of whole transcriptome at both gene and exon levels and with a unique ability of identifying novel splicing variants. To date, RNA-seq analysis of HBV-related hepatocellular carcinoma (HCC) has not been reported. In this study, we performed transcriptome analyses for 10 matched pairs of cancer and non-cancerous tissues from HCC patients on Solexa/Illumina GAII platform. On average, about 21.6 million sequencing reads and 10.6 million aligned reads were obtained for samples sequenced on each lane, which was able to identify >50% of all the annotated genes for each sample. Furthermore, we identified 1,378 significantly differently expressed genes (DEGs) and 24, 338 differentially expressed exons (DEEs). Comprehensive function analyses indicated that cell growth-related, metabolism-related and immune-related pathways were most significantly enriched by DEGs, pointing to a complex mechanism for HCC carcinogenesis. Positional gene enrichment analysis showed that DEGs were most significantly enriched at chromosome 8q21.3-24.3. The most interesting findings were from the analysis at exon levels where we characterized three major patterns of expression changes between gene and exon levels, implying a much complex landscape of transcript-specific differential expressions in HCC. Finally, we identified a novel highly up-regulated exon-exon junction in ATAD2 gene in HCC tissues. Overall, to our best knowledge, our study represents the most comprehensive characterization of HBV-related HCC transcriptome including exon level expression changes and novel splicing variants, which illustrated the power of RNA-seq and provided important clues for understanding the molecular mechanisms of HCC pathogenesis at system-wide levels.
Project description:<h4>Background</h4>Hepatocellular carcinoma (HCC), a major cause of cancer death in China, is preceded by chronic hepatitis and liver cirrhosis (LC). Although hepatitis B virus (HBV) has been regarded as a clear etiology of human hepatocarcinogenesis, the mechanism is still needs to be further clarified. In this study, we used a proteomic approach to identify the differential expression protein profiles between HCC and the adjacent non-tumorous liver tissues.<h4>Methods</h4>Eighteen cases of HBV-related HCC including 12 cases of LC-developed HCC and 6 cases of chronic hepatitis B (CHB)-developed HCC were analyzed by two-dimensional electrophoresis (2-DE) combined with matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS), and the results were compared to those of paired adjacent non-tumorous liver tissues.<h4>Results</h4>A total of 17 differentially expressed proteins with diverse biological functions were identified. Among these, 10 proteins were up-regulated, whereas the other 7 proteins were down-regulated in cancerous tissues. Two proteins, c-Jun N-terminal kinase 2 and ADP/ATP carrier protein were found to be up-regulated only in CHB-developed HCC tissues. Insulin-like growth factor binding protein 2 and Rho-GTPase-activating protein 4 were down-regulated in LC-developed and CHB-developed HCC tissues, respectively. Although 11 out of these 17 proteins have been already described by previous studies, or are already known to be involved in hepatocarcinogenesis, this study revealed 6 new proteins differentially expressed in HBV-related HCC.<h4>Conclusion</h4>These findings elucidate that there are common features between CHB-developed HCC and LC-developed HCC. The identified proteins are valuable for studying the hepatocarcinogenesis, and may be potential diagnostic markers or therapeutic targets for HBV-related HCC.
Project description:Tongue cancer is one of the most common types of cancer, but its molecular etiology and pathogenesis remain unclear. The aim of the present study was to elucidate the pathogenesis of tongue cancer and investigate novel potential diagnostic and therapeutic targets. Four matched pairs of tongue cancer and paracancerous tissues were collected for RNA sequencing (RNA?Seq), and the differentially expressed genes were analyzed. The RNA?Seq data of tongue cancer tissues were further analyzed using bioinformatics and reverse transcription?quantitative PCR analysis. The sequenced reads were quantified and qualified in accordance with the analysis demands. The transcriptomes of the tongue cancer tissues and paired paracancerous tissues were analyzed, and 1,700 upregulated and 2,249 downregulated genes were identified. Gene Ontology analysis uncovered a significant enrichment in the terms associated with extracellular matrix (ECM) organization, cell adhesion and collagen catabolic processes. Kyoto Encyclopedia of Genes and Genomes analysis demonstrated that these differentially expressed genes were mainly enriched in the focal adhesion pathway, ECM?receptor interaction pathway, phosphoinositide 3?kinase (PI3K)?Akt pathway, and cell adhesion molecules. Comprehensive analyses of the gene tree and pathway network revealed that the majority of cell cycle genes were upregulated, while the majority of the genes associated with intracellular response, cell adhesion and cell differentiation were downregulated. The ECM?receptor interaction, focal adhesion kinase (FAK) and PI3K?Akt pathways were closely associated with one another and held key positions in differential signaling pathways. The ECM?receptor, FAK and PI3K?Akt signaling pathways were found to synergistically promote tongue cancer occurrence and progression, and may serve as potential diagnostic and therapeutic targets for this type of cancer.
Project description:BACKGROUND:Hepatocellular carcinoma is the second most deadly cancer with late presentation and limited treatment options, highlighting an urgent need to better understand HCC to facilitate the identification of early-stage biomarkers and uncover therapeutic targets for the development of novel therapies for HCC. METHODS:Deep transcriptome sequencing of tumor and paired non-tumor liver tissues was performed to comprehensively evaluate the profiles of both the host and HBV transcripts in HCC patients. Differential gene expression patterns and the dys-regulated genes associated with clinical outcomes were analyzed. Somatic mutations were identified from the sequencing data and the deleterious mutations were predicted. Lastly, human-HBV chimeric transcripts were identified, and their distribution, potential function and expression association were analyzed. RESULTS:Expression profiling identified the significantly upregulated TP73 as a nodal molecule modulating expression of apoptotic genes. Approximately 2.5% of dysregulated genes significantly correlated with HCC clinical characteristics. Of the 110 identified genes, those involved in post-translational modification, cell division and/or transcriptional regulation were upregulated, while those involved in redox reactions were downregulated in tumors of patients with poor prognosis. Mutation signature analysis identified that somatic mutations in HCC tumors were mainly non-synonymous, frequently affecting genes in the micro-environment and cancer pathways. Recurrent mutations occur mainly in ribosomal genes. The most frequently mutated genes were generally associated with a poorer clinical prognosis. Lastly, transcriptome sequencing suggest that HBV replication in the tumors of HCC patients is rare. HBV-human fusion transcripts are a common observation, with favored HBV and host insertion sites being the HBx C-terminus and gene introns (in tumors) and introns/intergenic-regions (in non-tumors), respectively. HBV-fused genes in tumors were mainly involved in RNA binding while those in non-tumors tissues varied widely. These observations suggest that while HBV may integrate randomly during chronic infection, selective expression of functional chimeric transcripts may occur during tumorigenesis. CONCLUSIONS:Transcriptome sequencing of HCC patients reveals key cancer molecules and clinically relevant pathways deregulated/mutated in HCC patients and suggests that while HBV may integrate randomly during chronic infection, selective expression of functional chimeric transcripts likely occur during the process of tumorigenesis.
Project description:Chronic hepatitis B virus (HBV) is one of the leading causes of hepatocellular carcinoma (HCC). The precise molecular mechanisms by which HBV contributes to HCC development are not fully understood. The key genes and pathways involved in the transformation of nontumor hepatic tissues into HCC tissues in patients with HBV infection are essential to guide the treatment of HBV-associated HCC. Five datasets were collected from the Gene Expression Omnibus database to form a large cohort. Differentially expressed genes (DEGs) were identified between HCC tissues and nontumor hepatic tissues from HBV-infected patients using the 'limma' package. The top 50 upregulated and top 50 downregulated DEGs in HCC vs. nontumor tissues were demonstrated in subsets by heat maps. Based on the DEGs, Gene Ontology functional and Kyoto Encyclopedia of Genes and Genomes pathways enrichment analyses were performed. Several key pathways of the up- and downregulated DEGs were identified and presented by protein-protein interaction (PPI) networks. A total of 1,934 DEGs were identified. The upregulated DEGs were primarily associated with the 'cell cycle'. Among the DEGs enriched in the 'cell cycle' pathway, 6 genes had a log2-fold change >2: SFN, BUB1B, TTK, CCNB1, CDK1 and CDC20. The downregulated DEGs were primarily associated with the metabolic pathways, such as 'carbon metabolism', 'glycine, serine and threonine metabolism', 'tryptophan metabolism', 'retinol metabolism' and 'alanine, aspartate and glutamate metabolism'. The DEGs in the 'cell cycle' and 'metabolic pathways' were presented by the PPI networks respectively. Overall, the present study provides new insights into the specific etiology of HCC and molecular mechanisms for the transformation of nontumor hepatic tissues into HCC tissues in patients with a history of HBV infection and several potential therapeutic targets for targeted therapy in these patients.
Project description:<h4>Background</h4>Lung adenocarcinoma is the main pathological type of non-small cell lung cancer (NSCLC). In this study, we analyzed the gene expression profile of lung adenocarcinoma tumor and paracancerous tissues by bioinformatics to assess the genes and signal pathways related to lung adenocarcinoma.<h4>Methods</h4>The expression data of GSE7670, GSE27262, and GSE32863 were downloaded from the Gene Expression Omnibus (GEO) database. The three microarray data sets were integrated to obtain common differential expression genes of lung adenocarcinoma tumor and adjacent tissues. The STRING database was used to construct the protein-protein interaction (PPI) network of lung adenocarcinoma and mine the gene modules and core genes in the network, and the online tools, GEPIA and Kaplan-Meier plotter were used to further verify and analyze the core genes.<h4>Results</h4>There were 109 pairs of lung adenocarcinoma tissues and matched paracancerous normal lung tissues in the three data sets. Eighty-three differentially expressed genes were identified, including 16 up-regulated and 67 down-regulated genes, and 60 differentially expressed genes were successfully incorporated into the PPI network complex. Eleven core genes were identified in the PPI network complex, including three up-regulated (<i>COMP</i>, <i>SPP1</i>, <i>COL1A1</i>) and eight down-regulated genes (<i>CDH5</i>, <i>CAV1</i>, <i>CLDN5</i>, <i>LYVE1</i>, <i>IL6</i>, <i>VWF</i>, <i>TEK</i>, <i>PECAM1</i>). These core genes were verified by the GEPIA tumor database. Survival analysis showed that expression of the core genes was significantly related to the prognosis of lung adenocarcinoma. KEGG pathway analysis of core genes showed six genes (<i>COMP</i>, <i>SPP1</i>, <i>COL1A1</i>, <i>IL6</i>, <i>VWF</i>, <i>TEK</i>) were significantly enriched in the PI3K-Akt signaling-pathway (P=1.62E-06).<h4>Conclusions</h4>By analyzing the differential expression genes of lung adenocarcinoma and paracancerous normal tissues with bioinformatics, 11 genes with significant differential expression and significant influence on prognosis were identified. The findings may provide new concepts for developing diagnosis and treatment targets and prognosis markers for lung adenocarcinoma.