Bioinformatics Analysis of Differentially Expressed Rhythm Genes in Liver Hepatocellular Carcinoma.
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ABSTRACT:
SUBMITTER: Liu H
PROVIDER: S-EPMC8211427 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:AIM:To discover methylated-differentially expressed genes (MDEGs) in hepatocellular carcinoma (HCC) and to explore relevant hub genes and potential pathways. METHODS:The data of expression profiling GSE25097 and methylation profiling GSE57956 were gained from GEO Datasets. We analyzed the differentially methylated genes and differentially expressed genes online using GEO2R. Functional and enrichment analyses of MDEGs were conducted using the DAVID database. A protein-protein interaction (PPI) network was performed by STRING and then visualized in Cytoscape. Hub genes were ranked by cytoHubba, and a module analysis of the PPI network was conducted by MCODE in Cytoscape software. RESULTS:In total, we categorized 266 genes as hypermethylated, lowly expressed genes (Hyper-LGs) referring to endogenous and hormone stimulus, cell surface receptor linked signal transduction and behavior. In addition, 161 genes were labelled as hypomethylated, highly expressed genes (Hypo-HGs) referring to DNA replication and metabolic process, cell cycle and division. Pathway analysis illustrated that Hyper-LGs were enriched in cancer, Wnt, and chemokine signalling pathways, while Hypo-HGs were related to cell cycle and steroid hormone biosynthesis pathways. Based on PPI networks, PTGS2, PIK3CD, CXCL1, ESR1, and MMP2 were identified as hub genes for Hyper-LGs, and CDC45, DTL, AURKB, CDKN3, MCM2, and MCM10 were hub genes for Hypo-HGs by combining six ranked methods of cytoHubba. CONCLUSION:In the study, we disclose numerous novel genetic and epigenetic regulations and offer a vital molecular groundwork to understand the pathogenesis of HCC. Hub genes, including PTGS2, PIK3CD, CXCL1, ESR1, MMP2, CDC45, DTL, AURKB, CDKN3, MCM2, and MCM10, can be used as biomarkers based on aberrant methylation for the accurate diagnosis and treatment of HCC.
| S-EPMC6021769 | biostudies-literature
Project description:Aim: To explore gene expression profiling in hepatocellular carcinoma (HCC) cells exposed to swertiamarin. Methods: Cell viability, apoptosis and invasion were examined in HepG2 cells after swertiamarin treatment. Tumor growth of SK-Hep-1 cells xenografted in nude mice was monitored after swertiamarin treatment. Total RNA was isolated from HepG2 cells treated with swertiamarin for microarray analysis. The data of microarray were analyzed by bioinformatics. Results: Swertiamarin treatment decreased the viability and invasion while increased the apoptosis of HepG2 cells, and significantly inhibited the growth of SK-Hep-1 cells xenografted in nude mice. Pathway and biological process analysis of differentially expressed genes (DEGs) in swertiamarin treated HepG2 cells showed that PI3k-Akt was the most significant regulated pathway. 47 targets of swertiamarin were predicted by CGBVS while 21 targets were predicted by 3NN. Notably, 8 targets were predicted as the targets of swertiamarin by both programs, including two prominent targets JUN and STAT3. A large range of DEGs induced by swertiamarin could be regulated by JUN and STAT3. Conclusion: Swertiamarin treatment led to significant changes in the expression of a variety of genes that modulate cell survival, cell cycle progression, apoptosis, and invasion. Moreover, most of these genes can be clustered into pathway networks such as PI3K, JUN, STAT3, which are predicted targets of swertiamarin. Further confirmation of these targets will reveal the anti-tumor mechanisms of swertiamarin and facilitate the development of swertiamarin as a novel agent for cancer prevention and treatment.
| S-EPMC6856900 | biostudies-literature
Project description:ObjectiveFor the identification of abnormally methylated differentially expressed genes (MDEGs) in hepatocellular carcinoma (HCC), this study integrated four microarray datasets to investigate the fundamental mechanisms of tumorigenesis.MethodsWe obtained the expression (GSE76427, GSE57957) and methylation (GSE89852, GSE54503) profiles from Gene Expression Omnibus (GEO). The abnormally MDEGs were identified by using R software. We used the clusterProfiler package for the functional and pathway enrichment analysis. The String database was used to build the protein-protein interaction (PPI) network and visualize it in Cytoscape. MCODE was employed in the module analysis. Additionally, Gene Expression Profiling Interactive Analysis (GEPIA) and The Cancer Genome Atlas (TCGA) were employed to validate results. Lastly, we used cBioPortal software to examine the hub genetic alterations.ResultsWe identified 162 hypermethylated, down-regulated genes and 190 hypomethylated, up-regulated genes. Up-regulated genes with low methylation were enriched in biological processes, such as keratinocyte proliferation, and calcium homeostasis. Pathway analysis was enriched in the AMPK and PI3K-Akt signaling pathways. The PPI network identified PTK2, VWF, and ITGA2 as hypomethylated, high-expressing hub genes. Down-regulated genes with high methylation were related to responses to peptide hormones and estradiol, multi-multicellular organism process. Pathway analysis indicated enrichment in camp, oxytocin signaling pathways. The PPI network identified CFTR, ESR1, and CXCL12 as hypermethylated, low-expressing hub genes. Upon verification in TCGA databases, we found that the expression and methylation statuses of the hub genes changed significantly, and it was consistent with our results.ConclusionThe novel abnormally MDEGs and pathways in HCC were identified. These results helped us further understand the molecular mechanisms underlying HCC invasion, metastasis, and development. Hub genes can serve as biomarkers for an accurate diagnosis and treatment of HCC, and PTK2, VWF, ITGA2, CFTR, ESR1, and CXCL12 are included.
| S-EPMC7956867 | biostudies-literature
Project description:ObjectiveThe goal of this study was to understand the possible core genes associated with hepatocellular carcinoma (HCC) pathogenesis and prognosis.MethodsGEO contains datasets of gene expression, miRNA, and methylation patterns of diseased and healthy/control patients. The GSE62232 dataset was selected by employing the server Gene Expression Omnibus. A total of 91 samples were collected, including 81 HCC and 10 healthy samples as control. GSE62232 was analysed through GEO2R, and Functional Enrichment Analysis was performed to extract rational information from a set of DEGs. The Protein-Protein Relationship Networking search method has been used for extracting the interacting genes. MCC method was used to calculate the top 10 genes according to their importance. Hub genes in the network were analysed using GEPIA to estimate the effect of their differential expression on cancer progression.ResultsWe identified the top 10 hub genes through CytoHubba plugin. These included BUB1, BUB1B, CCNB1, CCNA2, CCNB2, CDC20, CDK1 and MAD2L1, NCAPG, and NDC80. NCAPG and NDC80 reported for the first time in this study while the remaining from a recently reported literature. The pathogenesis of HCC may be directly linked with the aforementioned genes. In this analysis, we found critical genes for HCC that showed recommendations for future prognostic and predictive biomarkers studies that could promote selective molecular therapy for HCC.
| S-EPMC9617698 | biostudies-literature
Project description:BackgroundExosomes are involved in cell-to-cell communication, neovascularization, cancer metastasis, and drug resistance, which all play an important role in the occurrence and progression of hepatocellular carcinoma (HCC). Because there are few mechanistic studies about the function of exosomes in HCC, the goals of this study were to identify exosome-related genes in HCC, to establish a reliable prognostic model for HCC, and to explore underlying mechanisms.MethodsThe exoRBase and The Cancer Genome Atlas (TCGA) databases were used to analyze differentially expressed genes (DEGs). Cox regression and least absolute shrinkage and selection operator analyses were used to identify DEGs closely related to the overall survival of patients with HCC. An exosome-related prognostic model was then constructed in TCGA and validated in the International Cancer Genome Consortium database. A nomogram was developed to predict survival. CIBERSORT was used to estimate the abundance of different types of immune cells. Immunotherapy-related DEGs were used to predict the effect of immunotherapy.ResultsForty-eight exosome-related DEGs were obtained; of them, five [exportin 1 (XPO1), lysosomal thiol reductase (IFI30), F-box protein 16 (FBXO16), calmodulin 1 (CALM1), MORC family CW-type zinc finger 3 (MORC3)] were selected to construct a predictive model. Patients with HCC were then divided into low- and high-risk groups using the best cut-off value, as determined by the X-tile software. Prognosis was significantly poorer in the high-risk than in the low-risk group (P=0.009; hazard ratio =2.65). Features related to exosomes were found to positively regulate immune response. Further analysis showed a higher risk score was associated with higher expression of immune checkpoint molecules, including programmed death ligand 1 (PD-L1), programmed death ligand 2 (PD-L2), T cell Ig and ITIM domain (TIGIT), and indoleamine-2,3-dioxygenase 1 (IDO1).ConclusionsThis study has identified a novel signature based on exosome-related genes that has potential as a prognostic biomarker for HCC. Our research provides an immunological perspective for the development of precision treatment for HCC.
| S-EPMC9403937 | biostudies-literature
Project description:Nasopharyngeal carcinoma (NPC) is a common malignancy of the head and neck. The aim of the present study was to conduct an integrated bioinformatics analysis of differentially expressed genes (DEGs) and to explore the molecular mechanisms of NPC. Two profiling datasets, GSE12452 and GSE34573, were downloaded from the Gene Expression Omnibus database and included 44 NPC specimens and 13 normal nasopharyngeal tissues. R software was used to identify the DEGs between NPC and normal nasopharyngeal tissues. Distributions of DEGs in chromosomes were explored based on the annotation file and the CYTOBAND database of DAVID. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were applied. Additionally, a protein-protein interaction (PPI) network, constructed using the STRING database and visualized by Cytoscape, was used to identify hub genes, key modules and important transcription factors (TFs). A total of 906 DEGs were identified; 434 (47.90%) DEGs were upregulated and 472 (52.10%) were downregulated. The DEGs were demonstrated to be enriched in chromosome 7p15-p14, 2q31, 1q21-q22, 1q21, 4q21 and 1p31-p22. DEGs were mainly enriched for the following GO terms: 'Cilium movement', 'microtubule bundle formation' and 'axoneme assembly'. KEGG pathway enrichment analysis revealed that pathways for 'cell cycle', 'DNA replication', 'interleukin-17 signaling', 'amoebiasis' and 'glutathione metabolism' were enriched. In addition, a PPI network comprising 867 nodes and 1,241 edges was constructed. Finally, five hub genes (aurora kinase A, cell division cycle 6, mitotic arrest deficient 2-like 1, DNA topoisomerase 2α and TPX2 microtubule nucleation factor), 8 modules, and 14 TFs were identified. Modules analysis revealed that cyclin-dependent kinase 1 and exportin 1 were involved in the pathway of Epstein-Barr virus infection. In summary, the hub genes, key modules and TFs identified in this study may promote our understanding of the pathogenesis of NPC and require further in-depth investigation.
| S-EPMC6546980 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) is a leading cause of cancer‑related morbidity and mortality globally. Despite the remarkable improvements in comprehensive HCC treatment, the underlying mechanistic details of HCC remain elusive. We screened HCC patients for differentially expressed genes (DEGs) using the Gene Expression Omnibus (GSE113850) and The Cancer Genome Atlas (TCGA) datasets. LINC01554 expression in 40 paired samples was determined by quantitative reverse transcription polymerase chain reaction (RT‑qPCR), and its clinical significance was assessed. LINC01554 was found to have a gain‑of‑function role in HCC in vitro. Additionally, the bioinformatics analysis of the genes co‑expressed with LINC01554 was performed using the Co‑LncRNA website, and potential molecular mechanisms were investigated using the Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes resources and validated by in vitro experiments. A total of 229 DEGs were identified from the GSE113850 dataset. Among the identified DEGs, three long non‑coding RNAs (lncRNAs) (DIO3OS, LINC01554, and LINC01093) with |logFC| ≥2 and P<0.05 were screened. A total of 148 lncRNAs with |logFC| ≥1 and P<0.05 were identified from TCGA dataset. Low LINC01554 expression levels were significantly correlated with overall survival, pathological stage, hepatitis B infection, tumour size, portal vein tumour thrombus, and TNM stage. Using gain‑of‑function assays, we further showed that LINC01554 inhibited the proliferation, migration, and invasion of the HCCLM9 and SK‑Hep1 cells and promoted G0/G1 arrest, but it did not significantly affect apoptosis. Western blotting revealed that LINC01554 overexpression resulted in increased ZO‑1 and E‑cadherin expression levels, but decreased N‑cadherin and vimentin expression levels. Moreover, LINC01554 overexpression inhibited Akt, p‑Akt, β‑catenin, and p‑Gsk3β expression. Our results showed that LINC01554 repressed HCC cell invasiveness and epithelial‑to‑mesenchymal transition partly by inhibiting Wnt and PI3K‑Akt signalling in vitro. Taken together, our findings provide new insights into the molecular mechanisms underlying HCC tumourigenesis and implicate LINC01554 as a potential target for HCC therapy.
| S-EPMC7551476 | biostudies-literature
Project description:Nonalcoholic fatty liver disease (NAFLD) is a global health problem characterized by excessive accumulation of fat in the liver without effect of other pathological factors including hepatitis infection and alcohol abuse. Current studies indicate that gene factors play important roles in the development of NAFLD. However, the molecular characteristics of differentially expressed genes (DEGs) and associated mechanisms with NAFLD have not been well elucidated. Using two microarray data associated with the gene expression profiling in liver tissues of NAFLD mice models, we identified and selected several common key DEGs that contributed to NAFLD. Based on bioinformatics analysis, we discovered that the DEGs were associated with a variety of biological processes, cellular components, and molecular functions and were also related to several significant pathways. Via pathway crosstalk analysis based on overlapping DEGs, we observed that the identified pathways could form large and complex crosstalk networks. Besides, large and complex protein interaction networks of DEGs were further constructed. In addition, many hub host factors with a high degree of connectivity were identified based on interaction networks. Furthermore, significant modules in interaction networks were found, and the DEGs in the identified modules were found to be enriched with distinct pathways. Taken together, these results suggest that the key DEGs, associated pathways, and modules contribute to the development of NAFLD and might be used as novel molecular targets for the treatment of NAFLD.
| S-EPMC6290321 | biostudies-literature
Project description:Cervical cancer is the most common gynecological malignancy. In recent years, the incidence of cervical cancer has had a younger trend. Cervical cancer morbidity and mortality rates have been significantly reduced due to recent decades of cervical cytology screening leading to the early detection and treatment of cervical cancer and precancerous lesions. There are a number of methods used to treat cervical cancer and improve the survival rate. However, the prevalence and recurrence rates of cervical cancer are increasing every year. There is an urgent requirement for a better understanding of the molecular mechanism cervical cancer development. The present study used scientific information retrieval from the Gene Expression Omnibus database to download the GSE26511 dataset, which contained 39 samples, including 19 cervical cancer lymph node-positive samples and 20 cervical cancer lymph node-negative samples. Using Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis, and weighted gene co-expression network analysis, 1,263 differentially expressed genes were found that affected the biological processes, including 'cell cycle process', 'signaling pathways', 'immune response', 'cell activation', 'regulation of immune system process' and 'inflammatory response'. These areas should be the focus of study for cervical cancer in the future.
| S-EPMC6036588 | biostudies-other
Project description:The aim of the current study was to investigate the molecular mechanisms underlying hepatitis C virus (HCV)-induced hepatocellular carcinoma (HCC) using the expression profiles of HCV-infected Huh7 cells at different time points. The differentially expressed genes (DEGs) were identified with the Samr package in R software once the data were normalized. Functional and pathway enrichment analysis of the identified DEGs was also performed. Subsequently, MCODE in Cytoscape software was applied to conduct module analysis of the constructed co-expression networks. A total of 1,100 DEGs were identified between the HCV-infected and control samples at 12, 18, 24 and 48 h post-infection. DEGs at 24 and 48 h were involved in the same signaling pathways and biological processes, including sterol biosynthetic processes and tRNA amino-acylation. There were 22 time series genes which were clustered into 3 expression patterns, and the demarcation point of the 2 expression patterns that 401 overlapping DEGs at 24 and 48 h clustered into was 24 h post-infection. tRNA synthesis-related biological processes emerged at 24 and 48 h. Replication and assembly of HCV in HCV-infected Huh7 cells occurred mainly at 24 h post-infection. In view of this, the screened time series genes have the potential to become candidate target molecules for monitoring, diagnosing and treating HCV-induced HCC.
| S-EPMC4237098 | biostudies-literature