Dataset Information

Bioinformatics analysis of LINC01554 and its co?expressed genes in hepatocellular carcinoma.

ABSTRACT: 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, ??catenin, and p?Gsk3? 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.

SUBMITTER: Li L

PROVIDER: S-EPMC7551476 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Bioinformatics analysis of LINC01554 and its co‑expressed genes in hepatocellular carcinoma.

Li Ling L Huang Kang K Lu Zhongshan Z Zhao Huijia H Li Hao H Ye Qifa Q Peng Guizhu G

Oncology reports 20200925 5

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 re ...[more]

PMID: 33000250

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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.

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.

Dataset Information

Bioinformatics analysis of LINC01554 and its co?expressed genes in hepatocellular carcinoma.

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Bioinformatics analysis of LINC01554 and its co‑expressed genes in hepatocellular carcinoma.

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