Dataset Information

Bioinformatic analysis of prognostic value of ZW10 interacting protein in lung cancer.

ABSTRACT: Background:ZWINT is a crucial component of the mitotic checkpoint. However, its possible role in lung cancer is unclear. In this study, we determined its correlation with lung cancer. Methods:Real-time PCR and immunohistochemistry (IHC) were used to determine 40 collected clinical lung cancer samples. Chi-square test was used to examine possible correlations between ZWINT expression and clinicopathological factors. The prognostic significance of mRNA expression of ZWINT in lung cancer was evaluated using the Kaplan-Meier plotter. Univariate and multivariate Cox proportional hazards regression analysis were performed to determine whether ZWINT is an independent risk factor for overall survival (OS) and disease-free survival (DFS) of lung cancer patients. Additionally, STRING database was used to analyze protein-protein interactions. Results:In this study, we screened 13 GSE datasets and detected that ZWINT is highly expressed in multiple carcinomas including lung, melanoma, prostate, nasopharyngeal, gastric, pancreatic, colon, esophageal, ovarian, renal, breast and liver cancer. Real-time PCR and IHC results of collected clinical lung cancer samples confirmed that ZWINT is highly expressed in tumor tissues compared with adjacent non-tumor tissues. Additionally, high expression of ZWINT might predict poor OS and DFS in lung cancer patients. Moreover, disease stage and expression level of ZWINT were correlated with recurrence-free survival and OS in lung cancer. Analysis of protein-protein interaction based on STRING database gained 8 top genes which could interact with ZWINT, including PMF1, MIS12, DSN1, ZW10, BUB1, BUB1B, CASC5, NDC80, NSL1 and NUF2. Conclusion:ZWINT is aberrantly highly expressed in lung tumor tissues and might be involved in the pathogenesis of lung cancer.

SUBMITTER: Yuan W

PROVIDER: S-EPMC5870638 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Bioinformatic analysis of prognostic value of ZW10 interacting protein in lung cancer.

Yuan Wen W Xie Songping S Wang Meng M Pan Shan S Huang Xiaoxing X Xiong Meng M Xiao Rui-Jing RJ Xiong Jie J Zhang Qiu-Ping QP Shao Liang L

OncoTargets and therapy 20180323

<h4>Background</h4>ZWINT is a crucial component of the mitotic checkpoint. However, its possible role in lung cancer is unclear. In this study, we determined its correlation with lung cancer.<h4>Methods</h4>Real-time PCR and immunohistochemistry (IHC) were used to determine 40 collected clinical lung cancer samples. Chi-square test was used to examine possible correlations between ZWINT expression and clinicopathological factors. The prognostic significance of mRNA expression of ZWINT in lung ca ...[more]

PMID: 29615843

Similar Datasets

Project description:Background:Lung cancer has been a common malignant tumor with a leading cause of morbidity and mortality, current molecular targets are woefully lacking comparing to the highly progressive cancer. The study is designed to identify new prognostic predictors and potential gene targets based on bioinformatic analysis of Gene Expression Omnibus (GEO) database. Methods:Four cDNA expression profiles GSE19188, GSE101929, GSE18842 and GSE33532 were chosen from GEO database to analyze the differently expressed genes (DEGs) between non-small cell lung cancer (NSCLC) and normal lung tissues. After the DEGs functions were analyzed, the protein-protein interaction network (PPI) of DEGs were constructed, and the core gene in the network which has high connectivity degree with other genes was identified. We analyzed the association of the gene with the development of NSCLC as well as its prognosis. Lastly we explored the conceivable signaling mechanism of the gene regulation during the development of NSCLC. Results:A total of 92 up regulated and 214 down regulated DEGs were shared in four cDNA expression profiles. Based on their PPI network, TOP2A was connected with most of other genes and was selected for further analysis. Kaplan-Meier overall survival analysis (OS) revealed that TOP2A was associated with worse NSCLC patients survival. And both GEPIA analysis and immunohistochemistry experiment (IHC) confirmed that TOP2A was aberrant gain of expression in cancer comparing to normal tissues. The clinical significance of TOP2A and probable signaling pathways it involved in were further explored, and a positive correlation between TOP2A and TPX2 expression was found in lung cancer tissues. Conclusion:Using bioinformatic analysis, we revealed that TOP2A could be adopted as a prognostic indicator of NSCLC and it potentially regulate cancer development through co-work with TPX2. However, more detailed experiments are needed to clarify its drug target role in clinical medical use.

Project description:The association between the expression of Lysyl oxidase (LOX) and its clinicopathological parameters and prognosis in patients with gastric cancer (GC) is still disputed. We performed this meta-analysis and bioinformatics analysis to clarify the relationship between the expression and methylation level of LOX with its clinicopathological parameters and prognostic value. We applied odds ratios with a 95% confidence interval to study the associations between LOX expression and clinicopathological parameters and overall survival (OS) in GC patients. In addition, association analysis of promoter methylation levels and expression of LOX with its prognostic value was performed using the Cancer Genome Atlas (TCGA) and four Gene Expression Omnibus (GEO) datasets. The PRISMA 2020 checklist was used to guide the data extraction and analysis. This meta-analysis includes seven clinical studies with a total of 1435 GC patients. LOX expression was related to lymph node metastasis and tumor distant metastasis in GC patients, but not to gender, tumor differentiation, Lauren classification, or tumor depth of invasion. Patients with GC grouped in high-expression of LOX had a much worse OS than those in low-expression. In addition, TCGA and four GEO datasets with 1279 samples were included in the bioinformatics analysis. The bioinformatics analysis showed that patients with high LOX levels had poor OS; low levels of methylation at some cg sites in the LOX gene were strongly related to poor OS and PFS; and methylation levels of LOX are negatively correlated with advanced tumor stage. The conclusion from comprehensive DNA methylation and gene expression analysis supports LOX as a specific diagnostic and prognosis biomarker in GC. LOX expression was related to lymph node metastasis, tumor distant metastasis and poor prognosis in GC. Low methylation levels were related to advanced tumor stage and poor prognosis in GC. Integrative analysis supports LOX as a specific diagnostic and prognosis biomarker in GC.

Project description:BackgroundUpregulation of the six-transmembrane epithelial antigen of prostate-1 (STEAP1) is closely associated with prognosis of numerous malignant cancers. However, its role in lung adenocarcinoma (LUAD), the most common type of lung cancer, remains unknown. This study aimed to investigate the role of STEAP1 in the occurrence and progression of LUAD and the potential mechanisms underlying its regulatory effects.MethodsSTEAP1 mRNA and protein expression were analyzed in 40 LUAD patients via real-time PCR and western blotting, respectively. We accessed the clinical data of 522 LUAD patients from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) to investigate the expression and prognostic role of STEAP1 in LUAD. Further, we performed gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and gene set enrichment analysis (GSEA) to elucidate the potential mechanism underlying the role of STEAP1 in LUAD. The protein-protein interaction (PPI) network of STEAP1 was analyzed using the Search Tool for the Retrieval of Interacting Genes (STRING) database, and hub genes with significant positive and negative associations with STEAP1 were identified and their role in LUAD prognosis was predicted.ResultsSTEAP1 was significantly upregulated in LUAD patients and associated with LUAD prognosis. Further, TCGA data indicated that STEAP1 upregulation is correlated with the clinical prognosis of LUAD. GO and KEGG analysis revealed that the genes co-expressed with STEAP1 were primarily involved in cell division, DNA replication, cell cycle, apoptosis, cytokine signaling, NF-kB signaling, and TNF signaling. GSEA revealed that homologous recombination, p53 signaling pathway, cell cycle, DNA replication, apoptosis, and toll-like receptor signaling were highly enriched upon STEAP1 upregulation. Gene Expression Profiling Interactive Analysis (GEPIA) analysis revealed that the top 10 hub genes associated with STEAP1 expression were also associated with the LUAD prognosis.ConclusionSTEAP1 upregulation potentially influences the occurrence and progression of LUAD and its co-expressed genes via regulation of homologous recombination, p53 signaling, cell cycle, DNA replication, and apoptosis. STEAP1 is a potential prognostic biomarker for LUAD.

Dataset Information

Bioinformatic analysis of prognostic value of ZW10 interacting protein in lung cancer.

Publications

Bioinformatic analysis of prognostic value of ZW10 interacting protein in lung cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets