Dataset Information

High Expression of UBB, RAC1, and ITGB1 Predicts Worse Prognosis among Nonsmoking Patients with Lung Adenocarcinoma through Bioinformatics Analysis.

ABSTRACT: Purpose:The molecular mechanism underlying the tumorigenesis and progression of lung adenocarcinoma (LUAD) in nonsmoking patients remains unclear. This study was conducted to select crucial therapeutic and prognostic biomarkers for nonsmoking patients with LUAD. Methods:Microarray datasets from the Gene Expression Omnibus (GSE32863 and GSE75037) were analyzed for differentially expressed genes (DEGs). Gene Ontology (GO) enrichment analysis of DEGs was performed, and protein-protein interaction network was then constructed using the Search Tool for the Retrieval of Interacting Genes and Cytoscape. Hub genes were then identified by the rank of degree. Overall survival (OS) analyses of hub genes were performed among nonsmoking patients with LUAD in Kaplan-Meier plotter. The Cancer Genome Atlas (TCGA) and The Human Protein Atlas (THPA) databases were applied to verify hub genes. In addition, we performed Gene Set Enrichment Analysis (GSEA) of hub genes. Results:We identified 1283 DEGs, including 743 downregulated and 540 upregulated genes. GO enrichment analyses showed that DEGs were significantly enriched in collagen-containing extracellular matrix and extracellular matrix organization. Moreover, 19 hub genes were identified, and 12 hub genes were closely associated with OS. Although no obvious difference was detected in ITGB1, the downregulation of UBB and upregulation of RAC1 were observed in LUAD tissues of nonsmoking patients. Immunohistochemistry in THPA database confirmed that UBB and ITGB1 were downregulated, while RAC1 was upregulated in LUAD. GSEA suggested that ribosome, B cell receptor signaling pathway, and cell cycle were associated with UBB, RAC1, and ITGB1 expression, respectively. Conclusions:Our study provides insights into the underlying molecular mechanisms of the carcinogenesis and progression of LUAD in nonsmoking patients and demonstrated UBB, RAC1, and ITGB1 as therapeutic and prognostic indicators for nonsmoking LUAD. This is the first study to report the crucial role of UBB in nonsmoking LUAD.

SUBMITTER: Deng H

PROVIDER: S-EPMC7593752 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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High Expression of <i>UBB</i>, <i>RAC1</i>, and <i>ITGB1</i> Predicts Worse Prognosis among Nonsmoking Patients with Lung Adenocarcinoma through Bioinformatics Analysis.

Deng Huan H Huang Yichao Y Wang Li L Chen Ming M Chen Ming M

BioMed research international 20201020

<h4>Purpose</h4>The molecular mechanism underlying the tumorigenesis and progression of lung adenocarcinoma (LUAD) in nonsmoking patients remains unclear. This study was conducted to select crucial therapeutic and prognostic biomarkers for nonsmoking patients with LUAD.<h4>Methods</h4>Microarray datasets from the Gene Expression Omnibus (GSE32863 and GSE75037) were analyzed for differentially expressed genes (DEGs). Gene Ontology (GO) enrichment analysis of DEGs was performed, and protein-protei ...[more]

PMID: 33134373

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Project description:BackgroundLung adenocarcinoma (LUAD) is the most common type of non-small cell lung cancer (NSCLC) with poor survival in advanced stage. Nowadays the rate of nonsmoking patients has dramatically increased and may be associated with the presence of driver mutations. Better understanding of the mutation profile data of nonsmoking LUAD patients are critical to predict survival and provide greater benefits to more patients. The apolipoprotein B mRNA editing enzyme catalytic polypeptide-like (APOBEC) has been shown to play an important role in molecular tumorigenesis of NSCLC. However, the clinical relevance of APOBEC in nonsmoking LUAD remains to be understood.MethodsLUAD patients with somatic mutation and RNA sequencing data obtained from The Cancer Genome Atlas (TCGA) were assessed and screened in the Gene Expression Omnibus. Transcriptome data and mutational signatures were analyzed using R package. Then, we used the least absolute shrinkage and selection operator (LASSO) regression model to construct the APOBEC3 score (APOBEC3 score) model. The prognostic value was evaluated using Kaplan-Meier analysis. Finally, the functional enrichment analysis of differential expressed genes (DEGs) and the immune-related features were also estimated using R package.ResultsBy analyzing the mutational profile data of NSCLC in the TCGA database, we found that different mutation patterns existed between smoking and nonsmoking patients, and the APOBEC3 family played an important role in the mutation pattern of nonsmoking patients with LUAD. We established an APOBEC3 score and found that TCW (W = A or T) mutation counts were significantly greater in the high APOBEC3 score group than in the low APOBEC3 score group. Furthermore, there were different immune feathers and prognostic values between the high and low APOBEC3 score patients, suggesting an independent prognostic factor of APOBEC3 in nonsmoking LUAD patients.ConclusionsWe established a comprehensive view of APOBEC3 mutations in nonsmoking LUAD patients. Our review provides new insights into using the APOBEC3 mutation to predict prognosis and improve the immunotherapy response for future applications.

Project description:BackgroundEarly-stage female lung adenocarcinoma is the most common type of lung cancer encountered in thoracic surgery departments. Tumor-node-metastasis (TNM) staging does not adequately explain a significant stratification phenomenon in the prognosis of patients with stage I lung adenocarcinoma. We aimed to investigate the contributory role of miR-940 in the prognosis prediction.MethodsWe analyzed the microRNA (miRNA) expression level in tumor tissues (high-risk group vs. low-risk group) from 12 non-smoking female patients with stage I lung adenocarcinoma using miRNA array. Bioinformatic analyses of miR-940 were also carried out based on the public database. Then, quantitative reverse-transcription polymerase chain reaction (qRT-PCR) tests of the tissue samples were further validated. And miR-940's function was analyzed and potential target genes were predicted.ResultsIn all, 24 miRNAs were found to be significantly different between the high-risk group and low-risk group. The expression level of miR-940 was lower in tumor tissue (P=0.011), and the survival rate in the high miR-940 group was higher [hazard ratio (HR) =0.688; P=0.011]. Gene Ontology (GO) analysis showed that the assembly functions of targets regulated by miR-940 were mainly enriched in regulation of myeloid cell differentiation, G1/S transition of mitotic cell cycle, and cellular response to environmental stimulus. miR-940 is involved in transforming growth factor-beta (TGF-beta) signaling pathway; TNF signaling pathway; and estrogen signaling pathway. The number of lung adenocarcinoma cells (A549) was significantly decreased after miR-940 was transfected. Ten epithelial-to-mesenchymal-transition (EMT)-associated genes (MMP9, ZEB1, CDH1, KRT8, KRT18 KET19, TWIST1, VIM, SNAI1, and SNAI2) were found to be significantly related to miR-940.ConclusionsThe present study showed that miR-940 might be a protective factor for positive prognosis in early stage nonsmoking female lung adenocarcinoma, with transforming growth factor-beta (TGF-beta) pathway, TNF pathway, and matrix metalloprotein (MMP9) being potential targets.

Project description:BackgroundInterleukin 6 (IL6) is both a pleiotropic cytokine and an immune-related gene. Interleukin 6 receptor (IL6R) is the receptor for IL6. It may be closely connected to the development of lung cancer. This research aims to explore the prognostic value of IL6R and prevent overtreatment of patients with lung adenocarcinoma (LUAD).MethodsIn this study, the expression of IL6R in tumor tissues and surrounding tissues was first analyzed by immunohistochemistry in the Affiliated Hospital of Nantong University (NTU) cohort. Secondly, we downloaded information from The Cancer Genome Atlas (TCGA) for the TCGA cohort and used this information to explore the messenger RNA (mRNA) level of IL6R. We then used Kaplan-Meier survival analyses, univariate and multivariate Cox analyses, nomogram models, and decision curve analyses to assess the prognostic value of IL6R. In addition, we also analyzed immune cell infiltration and the signaling pathways related to IL6R through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA).ResultsThrough the data analysis of the NTU cohort and the TCGA cohort, it was found that the expression of IL6R in normal tissues around the tumor was higher than that in tumor tissue, and was positively correlated with the overall survival (OS) of LUAD patients. Additionally, low expression of IL6R was found to be an independent predictor of poor prognosis among the patients in these two research cohorts. Next, using GO, KEGG, and GSEA analyses, we found that partially infiltrated tumor immune cells might be related to earlier staging and better prognosis of patients with LUAD. Finally, the study of the 3-5-year survival rate of LUAD patients through the nomogram showed that the expression of IL6R could improve the accuracy of prediction to prevent the overtreatment of some LUAD patients.ConclusionsIn summary, our study indicated that the low expression of IL6R was associated with poor prognosis among LUAD patients and that low expression of IL6R is a potential independent risk factor that could provide a basis for strengthening postoperative classification management of such patients.

Dataset Information

High Expression of UBB, RAC1, and ITGB1 Predicts Worse Prognosis among Nonsmoking Patients with Lung Adenocarcinoma through Bioinformatics Analysis.

Publications

High Expression of <i>UBB</i>, <i>RAC1</i>, and <i>ITGB1</i> Predicts Worse Prognosis among Nonsmoking Patients with Lung Adenocarcinoma through Bioinformatics Analysis.

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