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Cancer Immunology, Immunotherapy

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24.10.2019 | Original Article

Identification of prognostic genes in the acute myeloid leukemia immune microenvironment based on TCGA data analysis

verfasst von: Haimeng Yan, Jianwei Qu, Wen Cao, Yang Liu, Gaofeng Zheng, Enfan Zhang, Zhen Cai

Erschienen in: Cancer Immunology, Immunotherapy | Ausgabe 12/2019

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Abstract

Acute myeloid leukemia (AML) is a common and lethal hematopoietic malignancy that is highly dependent on the bone marrow (BM) microenvironment. Infiltrating immune and stromal cells are important components of the BM microenvironment and significantly influence the progression of AML. This study aimed to elucidate the value of immune/stromal cell-associated genes for AML prognosis by integrated bioinformatics analysis. We obtained expression profiles from The Cancer Genome Atlas (TCGA) database and used the ESTIMATE algorithm to calculate immune scores and stromal scores; we then identified differentially expressed genes (DEGs) based on these scores. Overall survival analysis was applied to reveal common DEGs of prognostic value. Subsequently, we conducted a functional enrichment analysis, generated a protein–protein interaction (PPI) network and performed an interrelation analysis of immune system processes, showing that these genes are mainly associated with the immune/inflammatory response. Finally, eight genes (CD163, CYP27A1, KCNA5, PPM1J, FOLR1, IL1R2, MYOF, VSIG2) were verified to be significantly associated with AML prognosis in the Gene Expression Omnibus (GEO) database. In summary, we identified key microenvironment-related genes that affect the outcomes of AML patients and might serve as therapeutic targets.

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Titel: Identification of prognostic genes in the acute myeloid leukemia immune microenvironment based on TCGA data analysis
verfasst von: Haimeng Yan
Jianwei Qu
Wen Cao
Yang Liu
Gaofeng Zheng
Enfan Zhang
Zhen Cai
Publikationsdatum: 24.10.2019
Verlag: Springer Berlin Heidelberg
Erschienen in: Cancer Immunology, Immunotherapy / Ausgabe 12/2019
Print ISSN: 0340-7004
Elektronische ISSN: 1432-0851
DOI: https://doi.org/10.1007/s00262-019-02408-7

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