Dataset Information

Identification of potential CpG sites for oral squamous cell carcinoma diagnosis via integrated analysis of DNA methylation and gene expression.

ABSTRACT:

Background

Oral squamous cell carcinoma (OSCC) accounts for more than 90% of the oral carcinomas and has a high fatality rate. This study aimed to identify potentially diagnostic biomarkers of OSCC through integrated analysis of DNA methylation and gene expression profiles.

Methods

The DNA methylation profiles of OSCC patients from The Cancer Genome Atlas (TCGA) were analyzed to screen patients with CpG island methylator phenotype (CIMP) and investigate the relationship between CIMP and survival probability of OSCC patients. Differential methylation and expression analyses of the paired OSCC tumor and paracancerous samples from TCGA were performed. Logistic regression model was established, and the accuracy of this diagnostic model for OSCC was evaluated in validation sets from Gene Expression Omnibus (GEO).

Results

OSCC patients with CIMP had lower survival probability than those without CIMP. The cg02860732 and cg04342955 were determined as candidate diagnostic methylation sites for OSCC. Logistic regression model was established based on cg02860732 and cg04342955 showed relatively high diagnostic accuracy in OSCC.

Conclusions

A diagnostic model for OSCC was identified based on the methylation sites cg02860732 and cg04342955, which might be favorable for the diagnosis of OSCC.

SUBMITTER: Chen L

PROVIDER: S-EPMC7816501 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

Identification of potential CpG sites for oral squamous cell carcinoma diagnosis via integrated analysis of DNA methylation and gene expression.

Chen Le L Wang Dong D

World journal of surgical oncology 20210119 1

<h4>Background</h4>Oral squamous cell carcinoma (OSCC) accounts for more than 90% of the oral carcinomas and has a high fatality rate. This study aimed to identify potentially diagnostic biomarkers of OSCC through integrated analysis of DNA methylation and gene expression profiles.<h4>Methods</h4>The DNA methylation profiles of OSCC patients from The Cancer Genome Atlas (TCGA) were analyzed to screen patients with CpG island methylator phenotype (CIMP) and investigate the relationship between CI ...[more]

PMID: 33468155

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Project description:BackgroundAberrant methylation plays an essential role in early cancer development. In this study, we investigated methylation patterns in lung squamous cell carcinoma (LUSC) and matched non-tumor tissue and plasma samples to evaluate the potential of these patterns in the diagnosis of LUSC.MethodsThe study group included 49 patients with stage I-III LUSC. We collected resected tumor tissue, paired peritumoral tissue, distant normal tissue, and corresponding plasma samples. A bespoke lung cancer bisulfite sequencing panel was used to profile the methylation level. Another 48 healthy volunteers provided control plasma samples.ResultsPeritumoral and distant normal tissues presented similar methylation signatures, distinct from those in tumor tissue samples. A comparison of methylation profiles led to the identification of 871 tumor-specific differentially methylated blocks, including 847 hypermethylated and 24 hypomethylated blocks (adjusted P value <0.05). All top-ranked blocks were tumor-related. Tissue samples were analyzed for field cancerization to identify progressively aggravating aberrant methylations during tumor initiation and development. The analysis revealed that 221 blocks presented a stepwise increase in methylation levels, while seven blocks presented a stepwise decrease in methylation pattern as the sampling drew nearer to the tumor. The malignant contaminated ratio (MCR) confirmed the presence of distinct methylation patterns between tumor and peritumoral tissue samples. We then constructed a diagnostic panel using a combined diagnostic score of cell-free DNA (cfDNA) that showed high sensitivity and specificity. The healthy controls had a significantly lower combined diagnostic score (cd-score) than LUSC patients. Additionally, based on the methylation profiles, LUSC could be classified into two subgroups, C1 and C2. The methylation profile of the C2 group was not distinct from the healthy controls, which had a significantly lower cd-score than did the C1 group.ConclusionsLUSC-specific methylation patterns could potentially discriminate between peritumoral tissue, distant normal tumor tissue, and tumor tissues. This preliminary study also supported the potential utility of cfDNA methylation analysis in diagnosing LUSC.

Project description:Background: Oral cancer is a frequently encountered neoplasm of the head and neck region, being the eighth most common type of human malignancy worldwide. Despite improvement in its control, morbidity and mortality, rates have improved little in the past decades. The present investigations about gene interaction and pathways still could not clear the appearance and development of oral squamous cell carcinoma (OSCC), completely. The aim of this study is to investigate the key genes and microRNAs interaction in OSCC. Materials and Methods: The microarray datasets GSE13601 and GSE98463, including mRNA and miRNA profiles, were extracted from the GEO database and were analyzed using GEO2R. Functional and pathway enrichment analyses were performed by using the DAVID database. The protein-protein interaction (PPI) network was constructed and analyzed using STRING database and Cytoscape software, respectively. Finally, miRDB was applied to predict the targets of the differentially expressed miRNAs (DEMs). Results: Totally, 97 differentially expressed genes (DEGs) were found in OSCC, including 66 up-regulated and 31 down-regulated genes. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses showed that up-regulated genes were significantly enriched in movement of cell or subcellular component, cell adhesion, biological adhesion, cellular localization, apoptotic signaling pathway, while the downregulated genes were enriched in muscle system process and oxidation-reduction process. From the PPI network, the top 10 nodes with the highest degree were detected as hub genes. In addition, 18 DEMs were screened, which included 7 up-regulated and 11 down-regulated miRNAs. STAT1 was potentially targeted by three miRNAs, including has-miR- 6825-5P, has-miR-4495, and has-miR-5580-3P. Conclusion: The roles of DEMs such as hsa-mir-5580-3p in OSCC through interactions with DEGs CD44, ACLY, ACTR3, STAT1, LAMC2 and YWHAZ may offer a suitable candidate biomarker pattern for diagnosis, prognosis and treatment processes in OSCC.

Project description:Oral squamous cell carcinoma (OSCC) is a life?threatening disease with a poor prognosis. Although previous studies have reported that the methylation of certain genes is associated with the pathogenesis of OSCC, the methylation of genes that have relevance to OSCC progression is not clearly documented. The present study aimed to gain insights into the mechanisms underlying DNA methylation regulation associated with OSCC progression and to identify potential prognostic markers for OSCC treatment. DNA methylation dataset GSE41114 and gene expression dataset GSE74530 were downloaded from the Gene Expression Omnibus database. The global methylation status of OSCC tumor samples and normal control samples was determined, and differentially methylated genes (DMGs) in OSCC samples compared with control samples were identified. The mRNA expression data were then integrated to identify differentially expressed genes (DEGs) in OSCC samples compared with control samples. Overlapping genes between DEGs and DMGs were identified, and functional enrichment analysis was performed. In addition, survival analysis of the overlapping genes was performed to screen genes with prognostic significance in OSCC. A total of 40,115 differential methylation CpG sites spanning 3,360 DMGs were identified; CpG sites in the promoter, gene body and intergenic regions were generally highly hypermethylated or hypomethylated. Additionally, 508 DEGs in OSCC samples were identified, including 332 upregulated and 176 downregulated genes. A total of 82 overlapping genes between DEGs and DMGs were found, which were mainly involved in protein metabolism, regulation of the metabolic process and the immune system. Additionally, differential methylation or expression of several genes, including fibroblast activation protein ? (FAP), interferon ? inducible protein 27 (IFI27), laminin subunit ?2 (LAMC2), matrix metallopeptidase 1 (MMP1), serine peptidase inhibitor Kazal?type 5 (SPINK5) and zinc finger protein 662 (ZNF662), was significantly associated with the survival of OSCC patients, and their differential expression in OSCC patients was further confirmed by reverse transcription?quantitative polymerase chain reaction in OSCC and normal oral cell lines. Overall, FAP, IFI27, LAMC2, MMP1, SPINK5 and ZNF662 genes caused by epigenetic changes via DNA methylation may be associated with the development and progression of OSCC, and should be valuable OSCC therapeutic biomarkers.

Dataset Information

Identification of potential CpG sites for oral squamous cell carcinoma diagnosis via integrated analysis of DNA methylation and gene expression.

Background

Methods

Results

Conclusions

Publications

Identification of potential CpG sites for oral squamous cell carcinoma diagnosis via integrated analysis of DNA methylation and gene expression.

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