Dataset Information

Elevated mRNA Levels of AURKA, CDC20 and TPX2 are associated with poor prognosis of smoking related lung adenocarcinoma using bioinformatics analysis.

ABSTRACT: Background and aim: Adenocarcinoma is a very common pathological subtype for lung cancer. We aimed to identify the gene signature associated with the prognosis of smoking related lung adenocarcinoma using bioinformatics analysis. Methods: A total of five gene expression profiles (GSE31210, GSE32863, GSE40791, GSE43458 and GSE75037) have been identified from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were analyzed using GEO2R software and functional and pathway enrichment analysis. Furthermore, the overall survival (OS) and recurrence-free survival (RFS) have been validated using an independent cohort from the Cancer Genome Atlas (TCGA) database. Results: We identified a total of 58 DEGs which mainly enriched in ECM-receptor interaction, platelet activation and PPAR signaling pathway. Then according to the enrichment analysis results, we selected three genes (AURKA, CDC20 and TPX2) for their roles in regulating tumor cell cycle and cell division. The results showed that the hazard ratio (HR) of the mRNA expression of AURKA for OS was 1.588 with (1.127-2.237) 95% confidence interval (CI) (P=0.009). The mRNA levels of CDC20 (HR 1.530, 95% CI 1.086-2.115, P=0.016) and TPX2 (HR 1.777, 95%CI 1.262-2.503, P=0.001) were also significantly associated with the OS. Expression of these three genes were not associated with RFS, suggesting that there might be many factors affect RFS. Conclusion: The mRNA signature of AURKA, CDC20 and TPX2 were potential biomarkers for predicting poor prognosis of smoking related lung adenocarcinoma.

SUBMITTER: Zhang MY

PROVIDER: S-EPMC6299412 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Elevated mRNA Levels of AURKA, CDC20 and TPX2 are associated with poor prognosis of smoking related lung adenocarcinoma using bioinformatics analysis.

Zhang Meng-Yu MY Liu Xiao-Xia XX Li Hao H Li Rui R Liu Xiao X Qu Yi-Qing YQ

International journal of medical sciences 20181105 14

<b>Background and aim:</b> Adenocarcinoma is a very common pathological subtype for lung cancer. We aimed to identify the gene signature associated with the prognosis of smoking related lung adenocarcinoma using bioinformatics analysis. <b>Methods:</b> A total of five gene expression profiles (GSE31210, GSE32863, GSE40791, GSE43458 and GSE75037) have been identified from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were analyzed using GEO2R software and funct ...[more]

PMID: 30588191

Similar Datasets

Project description:BackgroundIn this study, tumor microarray analysis was used to screen the key messenger RNAs (mRNAs) and microRNAs related to the progression of lung adenocarcinoma (LUAD), in order to provide a theoretical basis for early diagnosis, therapeutic targets, and prognosis evaluation of patients with LUAD.MethodsThe mRNA and miRNA expression datasets came from the Gene Expression Omnibus (GEO) project database. Differentially expressed genes (DEGs) and microRNAs (DEMs) between LUAD tissues and adjacent lung tissue were obtained using GEO2R. The Search Tool for the Retrieval of Interacting Genes website was also employed to construct and visualize the interactions of overlapped DEGs. The overall survival of DEMs was investigated using the Kaplan-Meier plotter. The TargetScan website (http://www.targetscan.org/) was used to verify the relationship between FA Complementation Group I (FANCI) and the expression of miRNA-218 (miR-218). The expression of FANCI was verified using the GEO and Human Protein Atlas databases, as well as Real Time Quantitative PCR using our own samples. Next, we analyzed the relationship between the expression of FANCI and the clinicopathological characteristics as well as the prognosis of patients with LUAD. We also explored whether the FANCI was related to immune cell infiltration in LUAD.ResultsFANCI was identified as a hub gene and associated with poor OS. We found that miR-218 negatively regulates FANCI mRNA expression. At the mRNA expression and protein level, FANCI was more highly expressed in LUAD tissues. The expression of FANCI in LUAD was related to tumor size (χ2=13.96, P<0.001), lymphatic metastasis (χ2=3.88, P<0.05), distant metastasis (χ2=45.39, P<0.001), and stage (χ2=11.03, P<0.05). In addition, the Cox regression model found that FANCI mRNA expression was an independent predictive factor of patient survival (P<0.05). FANCI expression was both weakly related to B cells and neutrophil infiltration in LUAD.ConclusionsmiR-218 may negatively regulate FANCI, and FANCI could promote metastasis via extracellular matrix (ECM) receptor interaction, leading to poor prognosis of LUAD. FANCI may be a key gene to the determine metastasis and poor prognosis in patients with LUAD. Changes in the immune microenvironment may be the mechanism through which FANCI leads to poor prognosis of LUAD.

Project description:Pancreatic ductal adenocarcinoma (PDAC) is a class of the commonest malignant carcinomas. The present study aimed to elucidate the potential biomarker and prognostic targets in PDAC. The array data of GSE41368, GSE43795, GSE55643, and GSE41369 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) and differentially expressed microRNAs (DEmiRNAs) in PDAC were obtained by using GEO2R, and overlapped DEGs were acquired with Venn Diagrams. Functional enrichment analysis of overlapped DEGs and DEmiRNAs was conducted with Metascape and FunRich, respectively. The protein-protein interaction (PPI) network of overlapped DEGs was constructed by STRING and visualized with Cytoscape. Overall survival (OS) of DEmiRNAs and hub genes were investigated by Kaplan-Meier (KM) plotter (KM plotter). Transcriptional data and correlation analyses among hub genes were verified through GEPIA and Human Protein Atlas (HPA). Additionally, miRNA targets were searched using miRTarBase, then miRNA-DEG regulatory network was visualized with Cytoscape. A total of 32 DEmiRNAs and 150 overlapped DEGs were identified, and Metascape showed that DEGs were significantly enriched in cellular chemical homeostasis and pathways in cancer, while DEmiRNAs were mainly enriched in signal transduction and Glypican pathway. Moreover, seven hub genes with a high degree, namely, V-myc avian myelocytomatosis viral oncogene homolog (MYC), solute carrier family 2 member 1 (SLC2A1), PKM, plasminogen activator, urokinase (PLAU), peroxisome proliferator activated receptor γ (PPARG), MET proto-oncogene, receptor tyrosine kinase (MET), and integrin subunit α 3 (ITGA3), were identified and found to be up-regulated between PDAC and normal tissues. miR-135b, miR-221, miR-21, miR-27a, miR-199b-5p, miR-143, miR-196a, miR-655, miR-455-3p, miR-744 and hub genes predicted poor OS of PDAC. An integrative bioinformatics analysis identified several hub genes that may serve as potential biomarkers or targets for early diagnosis and precision target treatment of PDAC.

Dataset Information

Elevated mRNA Levels of AURKA, CDC20 and TPX2 are associated with poor prognosis of smoking related lung adenocarcinoma using bioinformatics analysis.

Publications

Elevated mRNA Levels of AURKA, CDC20 and TPX2 are associated with poor prognosis of smoking related lung adenocarcinoma using bioinformatics analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets