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 PMID:32243356  

High GJB2 mRNA expression and its prognostic significance in lung adenocarcinoma: a study based on the TCGA database.

Yun Tang | You-Jing Zhang | Zeng-Hong Wu
Medicine | 2020

Lung adenocarcinoma (LUAD), a form of lung cancer, is reported to cause first and second-order cancer morbidity to men and women in China, respectively. We assessed the mRNA expression of GJB2 in LUAD patients in our study, based on data acquired from the cancer genome atlas (TCGA) and so as to increase further knowledge into the biological pathways involved in LUAD pathogenesis related to GJB2.Information on gene expression and comparing clinical data were recognized and downloaded from TCGA. Gene set enrichment analysis (GSEA) created an arranged list of all genes is indicated by their connection with GJB2 expression.Our study cohort included 265 (54.5%) female and 221 (36.0%) male patients. The scatter plot and paired plot showed the difference of GJB2 expression between normal and tumor samples (P < .01). Overall survival (OS) analysis demonstrated that LUAD with GJB2 -high had a more terrible prognosis than that with GJB2 -low (P < .01). Multivariate analysis with the cox proportional hazards model indicated that the expression of Cx26 (HR: 1.00; 95%CI: 1.00-1.01; P = .041) and stage (HR: 1.95; 95%CI: 1.23-3.09; P = .003) were independent prognostic factors for patients with LUAD. The GSEA results showed that cytosolic DNA sensing pathway, apoptosis, cytokine-cytokine receptor interaction, natural killer cell mediated cytotoxicity, regulation of actin cytoskeleton, toll-like receptor signaling pathway, small cell lung cancer and pathways in cancer are differentially enriched in GJB2 high expression phenotype.Our study confirmed the significantly high levels of Cx26 expression in LUAD patients with several observed clinical features. GJB2 may be a potentially useful prognostic molecular biomarker of bad survival in LUAD, while further experimental ought to be performed to demonstrate the biologic effect of GJB2.

Pubmed ID: 32243356

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This is a list of tools and resources that we have found mentioned in this publication.


Gene Set Enrichment Analysis (tool)

RRID:SCR_003199

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

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Bioconductor (tool)

RRID:SCR_006442

Software repository for R packages related to analysis and comprehension of high throughput genomic data. Uses separate set of commands for installation of packages. Software project based on R programming language that provides tools for analysis and comprehension of high throughput genomic data.

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