Bioinformatics and integrated analyses of prognosis-associated key genes in lung adenocarcinoma.

ABSTRACT:

Background

The objective of the present study was to predict candidate genes with prognostic information for lung adenocarcinoma (LUAD).

Methods

Weighted correlation network analysis (WGCNA) was utilized to build the co-expression network of deferentially expressed genes (DEGs) in GSE32863. Key genes were identified as the intersecting genes of the modules of WGCNA and DEGs. Kaplan-Meier plotter was employed to conduct survival analysis. Enrichment analysis was performed. The expression of key genes in LUAD was validated. Then, we performed in vitro experiments to explore functions of key genes. We overexpressed DYNLRB2 in A549 cell. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) and Western blotting were test expression levels and functional a

SUBMITTER: Zhu H 

PROVIDER: S-EPMC7947492 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature