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ABSTRACT: Background
With its diverse genetic foundation and heterogeneous nature, non-small cell lung cancer (NSCLC) needs a better comprehension of prognostic evaluation and efficient treatment targeting.Methods
Bioinformatics analysis was performed of The Cancer Genome Atlas (TCGA)-NSCLC and GSE68571 dataset. Overlapping differentially expressed genes (DEGs) were used for functional enrichment analysis and constructing the protein-protein interaction (PPI) network. In addition, key prognostic genes were identified through prognostic risk models, and their expression levels were verified. The phenotypic effects of cell division cycle 25C (CDC25C) regulation on NSCLC cell lines were assessed by in vitro experiments using various techniques such as flow cytometry, Trans
SUBMITTER: Meng J
PROVIDER: S-EPMC11002511 | biostudies-literature | 2024 Mar
REPOSITORIES: biostudies-literature