Dataset Information

Identification of Differentially Expressed Genes Induced by Aberrant Methylation in Oral Squamous Cell Carcinomas Using Integrated Bioinformatic Analysis.

ABSTRACT: Oral squamous cell carcinoma (OSCC) is a malignant disease. Methylation plays a key role in the etiology and pathogenesis of OSCC. The goal of this study was to identify aberrantly methylated differentially expressed genes (DEGs) in OSCCs, and to explore the underlying mechanisms of tumorigenesis by using integrated bioinformatic analysis. Gene expression profiles (GSE30784 and GSE38532) were analyzed using the R software to obtain aberrantly methylated DEGs. Functional enrichment analysis of screened genes was performed using the DAVID software. Protein?protein interaction (PPI) networks were constructed using the STRING database. The cBioPortal software was used to exhibit the alterations of genes. Lastly, we validated the results with the Cancer Genome Atlas (TCGA) data. Twenty-eight upregulated hypomethylated genes and 24 downregulated hypermethylated genes were identified. These genes were enriched in the biological process of regulation in immune response, and were mainly involved in the PI3K-AKT and EMT pathways. Additionally, three upregulated hypomethylated oncogenes and four downregulated hypermethylated tumor suppressor genes (TSGs) were identified. In conclusion, our study indicated possible aberrantly methylated DEGs and pathways in OSCCs, which could improve the understanding of the underlying molecular mechanisms. Aberrantly methylated oncogenes and TSGs may also serve as biomarkers and therapeutic targets for the precise diagnosis and treatment of OSCCs in the future.

SUBMITTER: Zhang X

PROVIDER: S-EPMC6032197 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Identification of Differentially Expressed Genes Induced by Aberrant Methylation in Oral Squamous Cell Carcinomas Using Integrated Bioinformatic Analysis.

Zhang Xiaoqi X Feng Hao H Li Dongfang D Liu Shanshan S Amizuka Norio N Li Minqi M

International journal of molecular sciences 20180607 6

Oral squamous cell carcinoma (OSCC) is a malignant disease. Methylation plays a key role in the etiology and pathogenesis of OSCC. The goal of this study was to identify aberrantly methylated differentially expressed genes (DEGs) in OSCCs, and to explore the underlying mechanisms of tumorigenesis by using integrated bioinformatic analysis. Gene expression profiles (GSE30784 and GSE38532) were analyzed using the R software to obtain aberrantly methylated DEGs. Functional enrichment analysis of sc ...[more]

PMID: 29875348

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Project description:BackgroundOral squamous cell carcinoma (OSCC) is a solid tumor, which originates from squamous epithelium, with about 400,000 new-cases/year worldwidely. Presently, chemoradiotherapy is the most important adjuvant treatment for OSCC, mostly in advanced tumors. However, clinical resistance to chemotherapy still leads to poor prognosis of OSCC patients. Via high-throughput analysis of gene expression database of OSCC, we investigated the molecular mechanisms underlying cisplatin resistance in OSCC, analyzing the differentially expressed genes (DEGs) and their regulatory relationship, to clarify the molecular basis of OSCC chemotherapy resistance and provide a theoretical foundation for the treatment of patients with OSCC and individualized therapeutic targets accurately.MethodsDatasets related to "OSCC" and "cisplatin resistance" (GSE111585 and GSE115119) were downloaded from the GEO database and analyzed by GEO2R. Venn diagram was used to obtain drug-resistance-related DEGs. Functional enrichment analysis and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were performed on DEGs using The Database for Annotation, Visualization and Integrated Discovery (DAVID) software. Protein-protein interaction (PPI) network was constructed by STRING (search tool for recurring instances of neighbouring genes) database. Potential target genes of miRNA were predicted via miRDB, and cBioportal was used to analyze the function and survival of the potential functional genes.ResultsForty-eight upregulated DEGs and 49 downregulated DEGs were obtained from the datasets, with cutoff as p < 0.01 and |log FC| > 1. The DEGs in OSCC mainly enriched in cell proliferation regulation, and chemokine activity. In PPI network with hub score > 300, the hub genes were identified as NOTCH1, JUN, CTNNB1, CEBPA, and ETS1. Among miRNA-mRNA targeting regulatory network, hsa-mir-200c-3p, hsa-mir-200b-3p, hsa-mir-429, and hsa-mir-139-5p were found to simultaneously regulate multiple hub genes. Survival analysis showed that patients with high CTNNB1 or low CEBPA expression had poor outcome.ConclusionsIn the OSCC cisplatin-resistant cell lines, NOTCH1, JUN, CTNNB1, CEBPA, and ETS1 were found as the hub genes involved in regulating the cisplatin resistance of OSCC. Members of the miR-200 family may reverse drug resistance of OSCC cells by regulating the hub genes, which can act as potential targets for the treatment of OSCC patients with cisplatin resistance.

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Project description:Background: Nasopharyngeal carcinoma (NPC) is an Epstein-Barr virus (EBV)-associated epithelial malignancy. Large-scale genetics or epigenetics studies of NPC have been relatively scarce and sporadic, and there are no effective targeted drugs for NPC. Integrative analysis of multiple different omics profiles has been proved to be an effective approach to shed new light on cancer. Methods: We developed a pipeline to aggregate consensus differentially expressed genes (DEGs) from multiple expression datasets from different platforms. Integrated bioinformatics analysis of DNA methylation and gene expression was used to prioritize key genes in NPC. We explored the biological and clinical importance of key genes, combining differential co-expression analysis, network analysis of protein-protein and microRNA (miRNA)-target interactions, and pan-cancer survival analysis. Results: We obtained 668 upregulated and 594 downregulated consensus DEGs, which enriched in the PI3K-AKT, NF-κB and immune-related pathways. In NPC, 98% of 3364 differentially methylated sites were hypermethylated. Actively expressed EBV gene EBNA1 was positively correlated with over-expressed genes coding DNA methyltransferase and Polycomb group proteins, suggesting that EBV infection may have an important role in the hypermethylation of NPC. Through integrated analysis of DNA methylation and mRNA and miRNA expression profiles, we prioritized 56 hypermethylated downregulated genes, including 7 tumor suppressor genes, and constructed a miRNA-target regulation network consisting of 12 hypermethylated miRNAs and 25 upregulated oncogenes. The promoter hypermethylation of PRKCB causing its downregulation was validated by experimental results and higher PRKCB expression was associated with longer overall survival in head-neck squamous cell carcinoma, suggesting the potential of PRKCB as a promising disease biomarker for NPC. Conclusions: Our integrative analysis provides reliable key genes for candidate biomarkers for diagnosis and prognosis in NPC. Based on the combined evidence of promoter hypermethylation, expression up-regulation, and association with overall survival, genes such as SCUBE2, PRKCB, IKZF1, MAP4K1, and GATA6 could be promising novel diagnostic biomarkers, and miRNAs including MIR150, MIR152, and MIR34 could be candidate prognosis biomarkers.

Dataset Information

Identification of Differentially Expressed Genes Induced by Aberrant Methylation in Oral Squamous Cell Carcinomas Using Integrated Bioinformatic Analysis.

Publications

Identification of Differentially Expressed Genes Induced by Aberrant Methylation in Oral Squamous Cell Carcinomas Using Integrated Bioinformatic Analysis.

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