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Identification of genes and analysis of prognostic values in nonsmoking females with non-small cell lung carcinoma by bioinformatics analyses.

ABSTRACT: Background:This study was performed to identify disease-related genes and analyze prognostic values in nonsmoking females with non-small cell lung carcinoma (NSCLC). Materials and methods:Gene expression profile GSE19804 was downloaded from the Gene Expression Omnibus (GEO) database and analyzed by using GEO2R. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used for the functional and pathway enrichment analysis. Then, the Search Tool for the Retrieval of Interacting Genes, Cytoscape, and Molecular Complex Detection were used to construct the protein-protein interaction (PPI) network and identify hub genes. Finally, the Kaplan-Meier plotter online tool was used for the overall survival analysis of hub genes. Results:A cohort of 699 differentially expressed genes was screened, and they were mainly enriched in the terms of ECM-receptor interaction, focal adhesion, and cell adhesion molecules. A PPI network was constructed, and 15 hub genes were identified base on the subset of PPI network. Then, two significant modules were detected and several genes were found to be associated with the cell cycle pathway. Finally, nine hub genes' (UBE2C, DLGAP5, TPX2, CCNB2, BIRC5, KIF20A, TOP2A, GNG11, and ANXA1) expressions were found to be associated with the prognosis of the patients. Conclusion:Overall, we propose that the cell cycle pathway may play an important role in nonsmoking females with NSCLC and the nine hub genes may be further explored as potential targets for NSCLC diagnosis and treatment.

SUBMITTER: Yang G

PROVIDER: S-EPMC6183654 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Identification of genes and analysis of prognostic values in nonsmoking females with non-small cell lung carcinoma by bioinformatics analyses.

Yang Guangda G Chen Qianya Q Xiao Jieming J Zhang Hailiang H Wang Zhichao Z Lin Xiangan X

Cancer management and research 20181008

<h4>Background</h4>This study was performed to identify disease-related genes and analyze prognostic values in nonsmoking females with non-small cell lung carcinoma (NSCLC).<h4>Materials and methods</h4>Gene expression profile GSE19804 was downloaded from the Gene Expression Omnibus (GEO) database and analyzed by using GEO2R. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used for the functional and pathway enrichment analysis. Then, the Search Tool for the Retrieval of Interacti ...[more]

PMID: 30349363

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Project description:Hepatocellular carcinoma (HCC) is a typical inflammation-driven cancer. Chronically unresolved inflammation may remodel the immunosuppressive tumor microenvironment, which is rich in innate immune cells. The mechanisms via which HCC progresses through the evasion of the innate immune surveillance remain unclear. The present study thus aimed to identify key genes involved in HCC immunosuppression and to establish an innate immune risk signature, with the ultimate goal of obtaining new insight into effective immunotherapies. HCC and normal liver tissue mRNA expression and clinicopathological data were obtained from the Cancer Genome Atlas database. The immunosuppressive innate immune-related genes (IIRGs) in HCC were screened using integrated bioinformatics analyses. Gene expression was then validated using the Gene Expression Omnibus database and the Human Protein Atlas database, and tissues were obtained from patients with HCC who underwent surgery. In total, 3,676 genes were identified as differentially expressed mRNAs after comparing the HCC tissues with the normal liver tissues in TCGA. Gene Set Enrichment Analyses revealed 21 highly expressed IIRGs in HCC tissues. A survival analysis and Cox regression model were used to construct an innate immune risk signature, including three IIRGs: Collectin-12 (COLEC12), matrix metalloproteinase-12 (MMP12) and mucin-12 (MUC12) genes. Univariate and multivariate Cox analyses revealed that the signature of the three IIRGs was a robust independent risk factor in relation to the overall survival (OS) of patients with HCC. The expression of the three aforementioned IIRGs was confirmed through external validation. Moreover, COLEC12 and MMP12 expression significantly correlated with that of immune checkpoint molecules or immunosuppressive cytokines. The tumor immune dysfunction and exclusion tool predicted that the increased expression of the three IIRGs in patients with HCC was significantly associated with the efficacy of relatively poor immune checkpoint blockade therapy. Conclusively, a novel innate immune-related risk signature for patients with HCC was constructed and validated. This signature may be involved in immunosuppression, and may be used to predict a poor prognosis, functioning as a potential immunotherapeutic target for patients with HCC.

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Identification of genes and analysis of prognostic values in nonsmoking females with non-small cell lung carcinoma by bioinformatics analyses.

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Identification of genes and analysis of prognostic values in nonsmoking females with non-small cell lung carcinoma by bioinformatics analyses.

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