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Immune profile of the tumor microenvironment and the identification of a four-gene signature for lung adenocarcinoma.


ABSTRACT: The composition and relative abundances of immune cells in the tumor microenvironment are key factors affecting the progression of lung adenocarcinomas (LUADs) and the efficacy of immunotherapy. Using the cancer gene expression dataset from The Cancer Genome Atlas (TCGA) program, we scored stromal and immune cells for tumor purity prediction by CIBERSORT and ESTMATE. Differential expression analysis was employed to identify 374 genes between the high-score group and the low-score group, which were utilized to conduct Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Protein-protein interaction (PPI) and Cox regression analysis were performed on the differentially expressed genes (DEGs) to identify four key tumor microenvironment (TME) -related genes (CCR2, CCR4, P2RY12, and P2RY13). The expression levels of the four DEGs differed significantly among LUAD patients of different ages, genders, and TNM stages. We found that the infiltration of resting memory CD4+ T cells, memory B cells, and M0 macrophages into the TME was co-regulated by these four DEGs. These four genes were closely related to the prognosis of LUAD and affected the infiltration of immune cells into the TME, which had predictive prognostic value in LUAD.

SUBMITTER: Fan T 

PROVIDER: S-EPMC7880407 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Immune profile of the tumor microenvironment and the identification of a four-gene signature for lung adenocarcinoma.

Fan Tao T   Zhu Mingchuang M   Wang Liyu L   Liu Yu Y   Tian He H   Zheng Yujia Y   Tan Fengwei F   Sun Nan N   Li Chunxiang C   He Jie J  

Aging 20201209 2


The composition and relative abundances of immune cells in the tumor microenvironment are key factors affecting the progression of lung adenocarcinomas (LUADs) and the efficacy of immunotherapy. Using the cancer gene expression dataset from The Cancer Genome Atlas (TCGA) program, we scored stromal and immune cells for tumor purity prediction by CIBERSORT and ESTMATE. Differential expression analysis was employed to identify 374 genes between the high-score group and the low-score group, which we  ...[more]

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