Mining Tcga Database to Screen Genes Valuable for Prognosis of Lung Cancer Microenvironment
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Fuyong Bian, Ming Zhang
Objective: To screen lncRNA related to microenvironment prognosis of lung cancer by mining TCGA database. Methods: 230 lung adenocarcinoma patients with both clinical prognosis information and methylation data were included through data connection using lung adenocarcinoma prognosis data downloaded from TCGA website and whole genome methylation data based on Illumina Methylation 450 chip. The R language was used for data combination, standardization and difference analysis, and SPSS 20.0 software was used for data analysis of differentially expressed genes to screen out specifically expressed transcription genes significantly related to lung cancer survival. Results Spearman rank correlation analysis screened out differential genes related to prognosis, and Kaplan Meier performed Log-rank test to screen out 2 genes closely related to prognosis of lung cancer patients. Cox multivariate regression analysis showed that DLX6 was more specific. Conclusion: Through the excavation of TCGA database in this study, it is preliminarily found that the methylation level of the methylation site of KRI1 gene has an impact on the prognosis of lung adenocarcinoma, which can be used as a biomarker for further study of lung cancer prognosis.
Tcga database, Microenvironmental prognosis of lung cancer, Transcription of genes, Mrna