Abstract:Abstract: In order to explore the internal mechanism of non-small cell lung cancer (NSCLC) from the genetic level, select genes related to the diagnosis and prognosis of NSCLC, and provide bioinformatics basis for further studing of the molecular mechanism of NSCLC, the data sets of GEO and TCGA databases were combined and analyzed by bioinformatics method to screen differentially expressed genes (DEGs) between NSCLC and normal lung tissues. Then, the Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), protein-protein interaction (PPI) analysis, ROC curve diagnosis efficiency analysis and LASSO survival analysis were carried out in the intersection of DEGs. A total of 240 DEGs were screened out, which were mainly involved in the biological processes of nuclear division and chromosome separation. GSEA analysis showed that the enrichment pathways were mainly linked to DNA repair and cell cycle. Twenty hub genes were screened out from PPI network. ROC results showed that UBE2C (AUC=0.939), TOP2A (AUC=0.927), RRM2 (AUC=0.927), CCNB1 (AUC=0.928), MKI67 (AUC=0.930), AURKA (AUC=0.931) and MELK (AUC=0.950) had relatively high diagnostic values. LASSO Cox regression showed that IL6, KIAA0101, MKI67, TPX2, AURKA, CDKN3 and CDCA5 were related to the prognosis of NSCLC patients. The results showed that ZWINT, KIF2C, MELK and CDCA5 may play an important role in NSCLC. This provides a new way to elucidate the molecular mechanism of NSCLC.
引用本文:
杨燕霞, 金 莲, 王 欣, 张 洁, 柳小平. 基于生物信息学分析的非小细胞肺癌诊断预后相关基因的筛选[J]. 生命科学研究, 2020, 24(2): 127-135.
YANG Yan-xia, JIN Lian, WANG Xin, ZHANG Jie, LIU Xiao-ping. Screening of Genes Related to Diagnosis and Prognosis of Non-small Cell Lung Cancer Based on Bioinformatics Analysis. Life Science Research, 2020, 24(2): 127-135.