Identification of Key Genes Related to Lung Squamous Cell Carcinoma Using Bioinformatics Analysis
Lung squamous cell carcinoma (LUSC) is often diagnosed at the advanced stage with poor prognosis. The mechanisms of its pathogenesis and prognosis require urgent elucidation. This study was performed to screen potential biomarkers related to the occurrence, development and prognosis of LUSC to revea...
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| Format: | Article |
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MDPI AG
2020-04-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/21/8/2994 |
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| author | Miaomiao Gao Weikaixin Kong Zhuo Huang Zhengwei Xie |
| author_facet | Miaomiao Gao Weikaixin Kong Zhuo Huang Zhengwei Xie |
| author_sort | Miaomiao Gao |
| collection | DOAJ |
| description | Lung squamous cell carcinoma (LUSC) is often diagnosed at the advanced stage with poor prognosis. The mechanisms of its pathogenesis and prognosis require urgent elucidation. This study was performed to screen potential biomarkers related to the occurrence, development and prognosis of LUSC to reveal unknown physiological and pathological processes. Using bioinformatics analysis, the lung squamous cell carcinoma microarray datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were analyzed to identify differentially expressed genes (DEGs). Furthermore, PPI and WGCNA network analysis were integrated to identify the key genes closely related to the process of LUSC development. In addition, survival analysis was performed to achieve a prognostic model that accomplished good prediction accuracy. Three hundred and thirty–seven up–regulated and 119 down-regulated genes were identified, in which four genes have been found to play vital roles in LUSC development, namely CCNA2, AURKA, AURKB, and FEN1. The prognostic model contained 5 genes, which were all detrimental to prognosis. The AUC of the established prognostic model for predicting the survival of patients at 1, 3, and 5 years was 0.692, 0.722, and 0.651 in the test data, respectively. In conclusion, this study identified several biomarkers of significant interest for additional investigation of the therapies and methods of prognosis of lung squamous cell carcinoma. |
| first_indexed | 2024-03-10T20:16:22Z |
| format | Article |
| id | doaj.art-66f3bb2d1e004aba914e92fdd392b557 |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-10T20:16:22Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-66f3bb2d1e004aba914e92fdd392b5572023-11-19T22:31:18ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672020-04-01218299410.3390/ijms21082994Identification of Key Genes Related to Lung Squamous Cell Carcinoma Using Bioinformatics AnalysisMiaomiao Gao0Weikaixin Kong1Zhuo Huang2Zhengwei Xie3Peking University International Cancer Institute and Department of Pharmacology, School of Basic Medical Sciences, Peking University, Beijing 100191, ChinaDepartment of Molecular and Cellular Pharmacology, School of Pharmaceutical Sciences, Peking University, Beijing 100191, ChinaDepartment of Molecular and Cellular Pharmacology, School of Pharmaceutical Sciences, Peking University, Beijing 100191, ChinaPeking University International Cancer Institute and Department of Pharmacology, School of Basic Medical Sciences, Peking University, Beijing 100191, ChinaLung squamous cell carcinoma (LUSC) is often diagnosed at the advanced stage with poor prognosis. The mechanisms of its pathogenesis and prognosis require urgent elucidation. This study was performed to screen potential biomarkers related to the occurrence, development and prognosis of LUSC to reveal unknown physiological and pathological processes. Using bioinformatics analysis, the lung squamous cell carcinoma microarray datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were analyzed to identify differentially expressed genes (DEGs). Furthermore, PPI and WGCNA network analysis were integrated to identify the key genes closely related to the process of LUSC development. In addition, survival analysis was performed to achieve a prognostic model that accomplished good prediction accuracy. Three hundred and thirty–seven up–regulated and 119 down-regulated genes were identified, in which four genes have been found to play vital roles in LUSC development, namely CCNA2, AURKA, AURKB, and FEN1. The prognostic model contained 5 genes, which were all detrimental to prognosis. The AUC of the established prognostic model for predicting the survival of patients at 1, 3, and 5 years was 0.692, 0.722, and 0.651 in the test data, respectively. In conclusion, this study identified several biomarkers of significant interest for additional investigation of the therapies and methods of prognosis of lung squamous cell carcinoma.https://www.mdpi.com/1422-0067/21/8/2994lung squamous carcinomabioinformaticsprognosis |
| spellingShingle | Miaomiao Gao Weikaixin Kong Zhuo Huang Zhengwei Xie Identification of Key Genes Related to Lung Squamous Cell Carcinoma Using Bioinformatics Analysis International Journal of Molecular Sciences lung squamous carcinoma bioinformatics prognosis |
| title | Identification of Key Genes Related to Lung Squamous Cell Carcinoma Using Bioinformatics Analysis |
| title_full | Identification of Key Genes Related to Lung Squamous Cell Carcinoma Using Bioinformatics Analysis |
| title_fullStr | Identification of Key Genes Related to Lung Squamous Cell Carcinoma Using Bioinformatics Analysis |
| title_full_unstemmed | Identification of Key Genes Related to Lung Squamous Cell Carcinoma Using Bioinformatics Analysis |
| title_short | Identification of Key Genes Related to Lung Squamous Cell Carcinoma Using Bioinformatics Analysis |
| title_sort | identification of key genes related to lung squamous cell carcinoma using bioinformatics analysis |
| topic | lung squamous carcinoma bioinformatics prognosis |
| url | https://www.mdpi.com/1422-0067/21/8/2994 |
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