Dataset Information

Expression and Bioinformatics-Based Functional Analysis of UAP1 in Lung Adenocarcinoma.

ABSTRACT: Background: Lung adenocarcinoma (LAD) is the most prevalent type of lung cancer. The abnormal expression of UDP-N-acetylglucosamine pyrophosphorylase 1 (UAP1) has been reported to be involved in many biological processes of cancer cells, but the expression of UAP1 in LAD is unclear.

Methods: Bioinformatics was used to analyse the LAD gene expression data and related clinical data in the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. DAVID6.8 was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) signal pathway enrichment analyses of UAP1 expression-related genes. The STRING database was used to analyse protein-protein interaction (PPI) networks. RNA isolation and reverse transcription-quantitative polymerase chain reaction (RT?qPCR) assay were used to detect the expression of UAP1 in tissues and blood samples.

Results: We found that UAP1 was upregulated in LAD tissues and correlated with poor clinical outcome. GO analysis showed that these genes were enriched in biological processes and functions including intracellular transport, cellular protein catabolic process, and mitochondria (P<0.05). The KEGG pathway analysis showed that these genes were mainly involved in the signalling pathways of amino sugar and nucleotide sugar metabolism, the aminoacyl-tRNA biosynthesis signalling pathway, and protein export (P<0.05). The PPI analysis showed that EPRS, COPB1, CCT3, ALDH18A1 and ARF1 genes had marked or potential interaction with UAP1 (P<0.01). In addition, UAP1 expression was upregulated in LAD tissues compared to normal tissues. High levels of UAP1 expression were associated with larger tumour sizes and later TNM stages. RT?qPCR detection in serum further showed that UAP1 expression was upregulated in the plasma of LAD patients compared to that of healthy volunteers. High expression of UAP1 in serum suggests a poor prognosis for LAD patients.

Conclusion: UAP1 could be a novel diagnostic biomarker and a promising therapeutic target for LAD.

SUBMITTER: Wang X

PROVIDER: S-EPMC7701148 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Expression and Bioinformatics-Based Functional Analysis of UAP1 in Lung Adenocarcinoma.

Wang Xianghai X Chen Xingwu X Liu Hongbing H

Cancer management and research 20201125

<h4>Background</h4>Lung adenocarcinoma (LAD) is the most prevalent type of lung cancer. The abnormal expression of UDP-N-acetylglucosamine pyrophosphorylase 1 (UAP1) has been reported to be involved in many biological processes of cancer cells, but the expression of UAP1 in LAD is unclear.<h4>Methods</h4>Bioinformatics was used to analyse the LAD gene expression data and related clinical data in the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. DAVID6.8 was used to ...[more]

PMID: 33269005

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Project description:Smoking is one of the most important factors associated with the development of lung cancer. However, the signaling pathways and driver genes in smoking-associated lung adenocarcinoma remain unknown. The present study analyzed 433 samples of smoking-associated lung adenocarcinoma and 75 samples of non-smoking lung adenocarcinoma from the Cancer Genome Atlas database. Gene Ontology (GO) analysis was performed using the Database for Annotation, Visualization and Integrated Discovery and the ggplot2 R/Bioconductor package. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed using the R packages RSQLite and org.Hs.eg.db. Multivariate Cox regression analysis was performed to screen factors associated with patient survival. Kaplan-Meier and receiver operating characteristic curves were used to analyze the potential clinical significance of the identified biomarkers as molecular prognostic markers for the five-year overall survival time. A total of 373 differentially expressed genes (DEGs; |log2-fold change|≥2.0 and P<0.01) were identified, of which 71 were downregulated and 302 were upregulated. These DEGs were associated with 28 significant GO functions and 11 significant KEGG pathways (false discovery rate <0.05). Two hundred thirty-eight proteins were associated with the 373 differentially expressed genes, and a protein-protein interaction network was constructed. Multivariate regression analysis revealed that 7 mRNAs, cytochrome P450 family 17 subfamily A member 1, PKHD1 like 1, retinoid isomerohydrolase RPE65, neurotensin receptor 1, fetuin B, insulin-like growth factor binding protein 1 and glucose-6-phosphatase catalytic subunit, significantly distinguished between non-smoking and smoking-associated adenocarcinomas. Kaplan-Meier analysis demonstrated that patients in the 7 mRNAs-high-risk group had a significantly worse prognosis than those of the low-risk group. The data obtained in the current study suggested that these genes may serve as potential novel prognostic biomarkers of smoking-associated lung adenocarcinoma.

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Dataset Information

Expression and Bioinformatics-Based Functional Analysis of UAP1 in Lung Adenocarcinoma.

Publications

Expression and Bioinformatics-Based Functional Analysis of UAP1 in Lung Adenocarcinoma.

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