Identifying M1-like macrophage related genes for prognosis prediction in lung adenocarcinoma based on a gene co-expression network.

ABSTRACT: Macrophages are one of the most important players in the tumor microenvironment. But the contribution of macrophages to lung adenocarcinoma (LUAD) is still controversial. The current study aimed to display an immune landscape to clarify the function of macrophages and detect prognostic hub genes in LUAD. The transcriptome data were adopted to screen differently expressed genes (DEGs) in The Cancer Genome Atlas database (TCGA). The cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm was used to reveal the immune landscape. Weighted gene co-expression network analysis (WGCNA) analysis was performed to identify the hub module associated with macrophages. Function Enrichment analysis was conducted on hub module genes. Moreover, univariate and multiv

SUBMITTER: Wang Z 

PROVIDER: S-EPMC9876840 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature