{"title":"通过综合生物信息学分析和实验验证发现AURKA是潜在的肺癌标志物。","authors":"Shan Shi, Yeqing Qiu, Zhongwen Jin, Jiao Zhou, Wenyan Yu, Hongyu Zhang","doi":"10.1615/CritRevEukaryotGeneExpr.2023046830","DOIUrl":null,"url":null,"abstract":"<p><p>Non-small-cell lung cancer (NSCLC) is a malignancy with high overall morbidity and mortality due to a lack of reliable methods for early diagnosis and successful treatment of the condition. We identified genes that would be valuable for the diagnosis and prognosis of lung cancer. Common DEGs (DEGs) in three GEO datasets were selected for KEGG and GO enrichment analysis. A protein-protein interaction (PPI) network was constructed using the STRING database, and molecular complex detection (MCODE) identified hub genes. Gene expression profiling interactive analysis (GEPIA) and the Kaplan-Meier method analyzed hub genes expression and prognostic value. Quantitative PCR and western blotting were used to test for differences in hub gene expression in multiple cell lines. The CCK-8 assay was used to determine the IC50 of the AURKA inhibitor CCT137690 in H1993 cells. Transwell and clonogenic assays validated the function of AURKA in lung cancer, and cell cycle experiments explored its possible mechanism of action. Overall, 239 DEGs were identified from three datasets. AURKA, BIRC5, CCNB1, DLGAP5, KIF11, and KIF15 had shown great potential for lung cancer diagnosis and prognosis. In vitro experiments suggested that AURKA significantly influenced the proliferation and migration of lung cancer cells and activities related to the dysregulation of the cell cycle. AURKA, BIRC5, CCNB1, DLGAP5, KIF11, and KIF15 may be critical genes that influence the occurrence, development, and prognosis of NSCLC. AURKA significantly affects the proliferation and migration of lung cancer cells by disrupting the cell cycle.</p>","PeriodicalId":56317,"journal":{"name":"Critical Reviews in Eukaryotic Gene Expression","volume":"33 5","pages":"39-59"},"PeriodicalIF":1.5000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AURKA Identified as Potential Lung Cancer Marker through Comprehensive Bioinformatic Analysis and Experimental Verification.\",\"authors\":\"Shan Shi, Yeqing Qiu, Zhongwen Jin, Jiao Zhou, Wenyan Yu, Hongyu Zhang\",\"doi\":\"10.1615/CritRevEukaryotGeneExpr.2023046830\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Non-small-cell lung cancer (NSCLC) is a malignancy with high overall morbidity and mortality due to a lack of reliable methods for early diagnosis and successful treatment of the condition. We identified genes that would be valuable for the diagnosis and prognosis of lung cancer. Common DEGs (DEGs) in three GEO datasets were selected for KEGG and GO enrichment analysis. A protein-protein interaction (PPI) network was constructed using the STRING database, and molecular complex detection (MCODE) identified hub genes. Gene expression profiling interactive analysis (GEPIA) and the Kaplan-Meier method analyzed hub genes expression and prognostic value. Quantitative PCR and western blotting were used to test for differences in hub gene expression in multiple cell lines. The CCK-8 assay was used to determine the IC50 of the AURKA inhibitor CCT137690 in H1993 cells. Transwell and clonogenic assays validated the function of AURKA in lung cancer, and cell cycle experiments explored its possible mechanism of action. Overall, 239 DEGs were identified from three datasets. AURKA, BIRC5, CCNB1, DLGAP5, KIF11, and KIF15 had shown great potential for lung cancer diagnosis and prognosis. In vitro experiments suggested that AURKA significantly influenced the proliferation and migration of lung cancer cells and activities related to the dysregulation of the cell cycle. AURKA, BIRC5, CCNB1, DLGAP5, KIF11, and KIF15 may be critical genes that influence the occurrence, development, and prognosis of NSCLC. AURKA significantly affects the proliferation and migration of lung cancer cells by disrupting the cell cycle.</p>\",\"PeriodicalId\":56317,\"journal\":{\"name\":\"Critical Reviews in Eukaryotic Gene Expression\",\"volume\":\"33 5\",\"pages\":\"39-59\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Critical Reviews in Eukaryotic Gene Expression\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1615/CritRevEukaryotGeneExpr.2023046830\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BIOTECHNOLOGY & APPLIED MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Critical Reviews in Eukaryotic Gene Expression","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1615/CritRevEukaryotGeneExpr.2023046830","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
AURKA Identified as Potential Lung Cancer Marker through Comprehensive Bioinformatic Analysis and Experimental Verification.
Non-small-cell lung cancer (NSCLC) is a malignancy with high overall morbidity and mortality due to a lack of reliable methods for early diagnosis and successful treatment of the condition. We identified genes that would be valuable for the diagnosis and prognosis of lung cancer. Common DEGs (DEGs) in three GEO datasets were selected for KEGG and GO enrichment analysis. A protein-protein interaction (PPI) network was constructed using the STRING database, and molecular complex detection (MCODE) identified hub genes. Gene expression profiling interactive analysis (GEPIA) and the Kaplan-Meier method analyzed hub genes expression and prognostic value. Quantitative PCR and western blotting were used to test for differences in hub gene expression in multiple cell lines. The CCK-8 assay was used to determine the IC50 of the AURKA inhibitor CCT137690 in H1993 cells. Transwell and clonogenic assays validated the function of AURKA in lung cancer, and cell cycle experiments explored its possible mechanism of action. Overall, 239 DEGs were identified from three datasets. AURKA, BIRC5, CCNB1, DLGAP5, KIF11, and KIF15 had shown great potential for lung cancer diagnosis and prognosis. In vitro experiments suggested that AURKA significantly influenced the proliferation and migration of lung cancer cells and activities related to the dysregulation of the cell cycle. AURKA, BIRC5, CCNB1, DLGAP5, KIF11, and KIF15 may be critical genes that influence the occurrence, development, and prognosis of NSCLC. AURKA significantly affects the proliferation and migration of lung cancer cells by disrupting the cell cycle.
期刊介绍:
Critical ReviewsTM in Eukaryotic Gene Expression presents timely concepts and experimental approaches that are contributing to rapid advances in our mechanistic understanding of gene regulation, organization, and structure within the contexts of biological control and the diagnosis/treatment of disease. The journal provides in-depth critical reviews, on well-defined topics of immediate interest, written by recognized specialists in the field. Extensive literature citations provide a comprehensive information resource.
Reviews are developed from an historical perspective and suggest directions that can be anticipated. Strengths as well as limitations of methodologies and experimental strategies are considered.