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Comprehensive bioinformatics analysis identifies several potential diagnostic markers and potential roles of cyclin family members in lung adenocarcinoma.

ABSTRACT: Purpose:The aim of this study was to identify critical genes in lung cancer progression. Methods:We downloaded and reanalyzed gene expression profiles from different public data-sets using comprehensive bioinformatics analysis. Differentially expressed genes (DEGs) were identified in lung adenocarcinoma tissues compared with adjacent nonmalignant lung tissues. The overlapping DEGs identified from different datasets were used for functional and pathway enrichment analyses and protein-protein interaction (PPI) analysis. Moreover, transcription factors (TFs) and miRNAs that regulated the overlapping DEGs were predicted, followed by a TF-miRNA-target network construction. Furthermore, survival analysis of genes was performed. Several genes were further validated by quantitative real-time PCR (qRT-PCR). Results:A total of 647 overlapping upregulated genes and 979 overlapping downregulated genes were identified. The overlapping upregulated genes and downregulated genes were involved in different functions, such as cell cycle, p53 signaling pathway, immune response, and cell adhesion molecules (CAMs). Several genes belonging to the cyclin family, including CCNB1, CCNB2, and CCNA2, were hubs of the PPI network and TF-miRNA-target network. Additionally, genes, including NPAS2, GNG7, CHIA, and SLC2A1, were predicted to be prognosis-related DEGs. Gene expression profiles determined by bioinformatics analysis and qRT-PCR were highly comparable. Conclusion:CCNB1, CCNB2, CCNA2, NPAS2, GNG7, CHIA, and SLC2A1 are promising targets for the clinical diagnosis and therapy of lung adenocarcinoma.

SUBMITTER: Gao LW

PROVIDER: S-EPMC6204853 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Comprehensive bioinformatics analysis identifies several potential diagnostic markers and potential roles of cyclin family members in lung adenocarcinoma.

Gao Li-Wei LW Wang Guo-Liang GL

OncoTargets and therapy 20181024

<h4>Purpose</h4>The aim of this study was to identify critical genes in lung cancer progression.<h4>Methods</h4>We downloaded and reanalyzed gene expression profiles from different public data-sets using comprehensive bioinformatics analysis. Differentially expressed genes (DEGs) were identified in lung adenocarcinoma tissues compared with adjacent nonmalignant lung tissues. The overlapping DEGs identified from different datasets were used for functional and pathway enrichment analyses and prote ...[more]

PMID: 30425528

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Project description:BACKGROUND:Rhabdomyosarcoma (RMS), a common soft-tissue malignancy in pediatrics, presents high invasiveness and mortality. However, besides known changes in the PAX3/7-FOXO1 fusion gene in alveolar RMS, the molecular mechanisms of the disease remain incompletely understood. The purpose of the study is to recognize potential biomarkers related with RMS and analyse their molecular mechanism, diagnosis and prognostic significance. METHODS:The Gene Expression Omnibus was used to search the RMS and normal striated muscle data sets. Differentially expressed genes (DEGs) were filtered using R software. The DAVID has become accustomed to performing functional annotations and pathway analysis on DEGs. The protein interaction was constructed and further processed by the STRING tool and Cytoscape software. Kaplan-Meier was used to estimate the effect of hub genes on the ending of sarcoma sufferers, and the expression of these genes in RMS was proved by real-time polymerase chain reaction (RT-PCR). Finally, the expression of CDK1 and CCNB1 in RMS was validated by immunohistochemistry (IHC). RESULTS:A total of 1932 DEGs were obtained, amongst which 1505 were up-regulated and 427were down-regulated. Up-regulated genes were largely enriched in the cell cycle, ECM-receptor interaction, PI3K/Akt and p53 pathways, whilst down-regulated genes were primarily enriched in the muscle contraction process. CDK1, CCNB1, CDC20, CCNB2, AURKB, MAD2L1, HIST2H2BE, CENPE, KIF2C and PCNA were identified as hub genes by Cytoscape analyses. Survival analysis showed that, except for HIST2H2BE, the other hub genes were highly expressed and related to poor prognosis in sarcoma. RT-PCR validation showed that CDK1, CCNB1, CDC20, CENPE and HIST2H2BE were significantly differential expression in RMS compared to the normal control. IHC revealed that the expression of CDK1 (28/32, 87.5%) and CCNB1 (26/32, 81.25%) were notably higher in RMS than normal controls (1/9, 11.1%; 0/9, 0%). Moreover, the CCNB1 was associated with the age and location of the patient's onset. CONCLUSIONS:These results show that these hub genes, especially CDK1 and CCNB1, may be potential diagnostic biomarkers for RMS and provide a new perspective for the pathogenesis of RMS.

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Comprehensive bioinformatics analysis identifies several potential diagnostic markers and potential roles of cyclin family members in lung adenocarcinoma.

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Comprehensive bioinformatics analysis identifies several potential diagnostic markers and potential roles of cyclin family members in lung adenocarcinoma.

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