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pmid:29875348

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

Xiaoqi Zhang · Hao Feng · Dongfang Li · Shanshan Liu · Norio Amizuka · Minqi Li

International journal of molecular sciences · 2018 doi:10.3390/ijms19061698

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Experiment

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Data

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Analysis

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title
Identification of Differentially Expressed Genes Induced by Aberrant Methylation in Oral Squamous Cell Carcinomas Using Integrated Bioinformatic Analysis.
doi
10.3390/ijms19061698
pmid
29875348
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Xiaoqi Zhang
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Hao Feng
[2]
Dongfang Li
[3]
Shanshan Liu
[4]
Norio Amizuka
[5]
Minqi Li
journal
International journal of molecular sciences
year
2018
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.
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ABL2 was significantly associated with overall survival in head and neck squamous cell carcinoma (HNSC) patients, using a Kaplan–Meier curve and a log-rank test.
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ABL2 was significantly associated with overall survival in head and neck squamous cell carcinoma (HNSC) patients, using a Kaplan–Meier curve and a log-rank test.
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sections[11] "4.1. Microarray Data Information" paragraph 2
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In this study, the gene-expression-profiling dataset (GSE30784) and the gene-methylation-profile dataset (GSE38532) were obtained from the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/) of NCBI.
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ABL2 was significantly associated with overall survival in head and neck squamous cell carcinoma (HNSC) patients, using a Kaplan–Meier curve and a log-rank test.
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In this study, the gene-expression-profiling dataset (GSE30784) and the gene-methylation-profile dataset (GSE38532) were obtained from the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/) of NCBI.
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ABL2 was significantly associated with overall survival in head and neck squamous cell carcinoma (HNSC) patients, using a Kaplan–Meier curve and a log-rank test.
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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. 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