Objective: To determine the prognostic significance of inflammatory response-associated genes in acute myeloid leukemia (AML).
Methods: Transcriptomic profiles and related clinical information of AML patients were acquired from a public database. To establish a multi-gene prognosis signature, we performed least absolute shrinkage and selection operator Cox analysis for the TCGA cohort and evaluated the ICGC cohort for verification. Subsequently, Kaplan-Meier analysis was carried out to compare the overall survival (OS) rates between high- and low-risk groups. Biological function and single-sample gene set enrichment (ssGSEA) analyses were employed to investigate the association of risk score with immune status and the tumor microenvironment. Prognostic gene expression levels in AML samples and normal controls were confirmed by qRT-PCR and immunofluorescence.
Results: We identified a potential inflammatory response-related signature comprising 11 differentially expressed genes, including ACVR2A, CCL22, EBI3, EDN1, FFAR2, HRH1, ICOSLG, IL-10, INHBA, ITGB3, and LAMP3, and found that AML patients with high expression levels in the high-risk group had poor OS rates. Biological function analyses revealed that prognostic genes mainly participated in inflammation and immunity signaling pathways. Analyses of cancer-infiltrating immunocytes indicated that in high-risk patients, the immune suppressive microenvironment was significantly affected. The expression of the inflammation reaction-associated signature was found to be associated with susceptibility to chemotherapy. There was a significant difference in prognostic gene expression between AML and control tissues.
Conclusion: A novel inflammatory response-related signature was developed with 11 candidate genes to predict prognosis and immune status in AML patients.
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Cytokine
January 2025
School of Basic Medical College, Beihua University, Jilin 132013, China. Electronic address:
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December 2024
College of Veterinary Medicine, China Agricultural University, 100193, Beijing, China. Electronic address:
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April 2024
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medRxiv
November 2024
Nutrition Epidemiology and Data Science, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA.
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