Identification of KIF4A and its effect on the progression of lung adenocarcinoma based on the bioinformatics analysis.

ABSTRACT:

Background

Lung adenocarcinoma (LUAD) is the most frequent histological type of lung cancer, and its incidence has displayed an upward trend in recent years. Nevertheless, little is known regarding effective biomarkers for LUAD.

Methods

The robust rank aggregation method was used to mine differentially expressed genes (DEGs) from the gene expression omnibus (GEO) datasets. The Search Tool for the Retrieval of Interacting Genes (STRING) database was used to extract hub genes from the protein-protein interaction (PPI) network. The expression of the hub genes was validated using expression profiles from TCGA and Oncomine databases and was verified by real-time quantitative PCR (qRT-PCR). The module and survival analyses of the hub genes were determined using Cytoscape and Kapla

SUBMITTER: Song Y 

PROVIDER: S-EPMC7823194 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature