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Upregulation of desmoglein 2 and its clinical value in lung adenocarcinoma: a comprehensive analysis by multiple bioinformatics methods.

ABSTRACT: Background:Desmoglein-2 (DSG2), a desmosomal adhesion molecule, is found to be closely related to tumorigenesis in recent years. However, the clinical value of DSG2 in lung adenocarcinoma remains unclear. Methods:Real-time reverse transcription-quantitative polymerase chain reaction (qRT-PCR) was utilized to detect the expression of DSG2 in 40 paired lung adenocarcinoma tissues and corresponding non-cancerous tissues. Data from The Cancer Genome Atlas (TCGA) and Oncomine datasets were also downloaded and analyzed. The correlation between DSG2 and clinicopathological features was investigated. The expression of DSG2 protein by immunohistochemical was also detected from tissue microarray and the Human Protein Atlas database. Integrated meta-analysis combining the three sources (qRT-PCR data, TCGA data and Oncomine datasets) was performed to evaluate the clinical value of DSG2. Univariate and multivariate Cox regression analyses were used to explore the prognostic value of DSG2. Then, co-expressed genes were calculated by Pearson correlation analysis. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to investigate the underlying molecular mechanism. The expression level in lung adenocarcinoma and prognostic significance of the top ten co-expressed genes were searched from Gene Expression Profiling Interactive Analysis (GEPIA) online database. Results:DSG2 was highly expressed in lung adenocarcinoma tissues based on qRT-PCR, TCGA and Oncomine datasets. The protein expression of DSG2 was also higher in lung adenocarcinoma. According to qRT-PCR and TCGA, high DSG2 expression was positively associated with tumor size (p = 0.027, p = 0.001), lymph node metastasis (p = 0.014, p < 0.001) and TNM stage (p = 0.023, p < 0.001). The combined standard mean difference values of DSG2 expression based on the three sources were 1.30 (95% confidence interval (CI): 1.08-1.52) using random effect model. The sensitivity and specificity were 0.73 (95% CI [0.69-0.76]) and 0.96 (95% CI [0.89-0.98]). The area under the curve based on summarized receiver operating characteristic (SROC) curve was 0.79 (95% CI [0.75-0.82]). Survival analysis revealed that high DSG2 expression was associated with a short overall survival (hazard ratio [HR] = 1.638; 95% CI [1.214-2.209], p = 0.001) and poor progression-free survival (HR = 1.475; 95% CI [1.102-1.974], p < 0.001). A total of 215 co-expressed genes were identified. According to GO and KEGG analyses, these co-expressed genes may be involved in "cell division", "cytosol", "ATP binding" and "cell cycle". Based on GEPIA database, seven of the top ten co-expressed genes were highly expressed in lung adenocarcinoma (DSC2, SLC2A1, ARNTL2, ERO1L, ECT2, ANLN and LAMC2). High expression of these genes had shorter overall survival. Conclusions:The expression of DSG2 is related to the tumor size, lymph node metastasis and TNM stage. Also, DSG2 predicts poor prognosis in lung adenocarcinoma.

SUBMITTER: Sun R

PROVIDER: S-EPMC7024574 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Upregulation of desmoglein 2 and its clinical value in lung adenocarcinoma: a comprehensive analysis by multiple bioinformatics methods.

Sun Ruiying R Ma Chao C Wang Wei W Yang Shuanying S

PeerJ 20200213

<h4>Background</h4>Desmoglein-2 (DSG2), a desmosomal adhesion molecule, is found to be closely related to tumorigenesis in recent years. However, the clinical value of DSG2 in lung adenocarcinoma remains unclear.<h4>Methods</h4>Real-time reverse transcription-quantitative polymerase chain reaction (qRT-PCR) was utilized to detect the expression of DSG2 in 40 paired lung adenocarcinoma tissues and corresponding non-cancerous tissues. Data from The Cancer Genome Atlas (TCGA) and Oncomine datasets ...[more]

PMID: 32095325

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Project description:BackgroundLung cancer is one of the most common malignant tumors in the world. Exportins are closely associated with the cellular activity and disease progression in a variety of different tumors. However, the expression level, genetic variation, immune infiltration, and biological function of different exportins in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), as well as their relationship with the prognosis of patients with LUAD and LUSC have not been fully clarified.MethodsTo analyze the differential expression, prognostic value, genetic variation, biological function, and immune cell infiltration of exportins in patients with LUAD and LUSC, the ONCOMINE; UALCAN; Human Protein Atlas (HPA); Kaplan-Meier plotter; cBioPortal; Search Tool for the Retrieval of Interacting Genes/Proteins (STRING); Database for Annotation, Visualization, and Integrated Discovery (DAVID); Tumor Immune Estimation Resource (TIMER); and LinkedOmics databases were used in this study.ResultsThe transcriptional and protein expression levels of CSE1L and XPO1/5/6/7 were increased in patients with LUAD and LUSC, and the increased transcriptional levels of CSE1L and XPO5/6/7 were related to worse prognosis. An increased transcriptional level of XPO1 was associated with a better prognosis. These results indicated that CSE1L and XPO1/5/6/7 may be potential prognostic biomarkers for the survival of patients with LUAD and LUSC. Moreover, the high mutation rate of exportins in non-small cell lung cancer was 50.48%, and the largest proportion of mutations included high messenger RNA expression. The expression of exportins was significantly correlated with the infiltration of various immune cells. Differentially expressed exportins could regulate the occurrence and development of LUAD and LUSC by involving a variety of microRNAs and transcription factor E2F1.ConclusionsOur study provides novel insights into the selection of prognostic biomarkers of exportins in LUAD and LUSC.

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Dataset Information

Upregulation of desmoglein 2 and its clinical value in lung adenocarcinoma: a comprehensive analysis by multiple bioinformatics methods.

Publications

Upregulation of desmoglein 2 and its clinical value in lung adenocarcinoma: a comprehensive analysis by multiple bioinformatics methods.

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