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Prognostic role of chemokine-related genes in acute myeloid leukemia. | LitMetric

AI Article Synopsis

  • Chemotactic cytokines are key players in the development of acute myeloid leukemia (AML), making it important to explore chemotactic cytokine-related genes (CCRGs) and their mechanisms in this disease.
  • Using various datasets, researchers identified 29 differentially expressed CCRGs and found that these genes mainly relate to chemotactic functions. They developed a prognostic model incorporating six key genes that show significant association with AML patient survival.
  • Survival analysis indicated notable differences in overall survival based on the expression levels of the prognostic genes, and immune cell analysis revealed correlations between specific CCRGs and different types of immune cells within the tumor environment.

Article Abstract

Background: Chemotactic cytokines play a crucial role in the development of acute myeloid leukemia (AML). Thus, investigating the mechanisms of chemotactic cytokine-related genes (CCRGs) in AML is of paramount importance.

Methods: Using the TCGA-AML, GSE114868, and GSE12417 datasets, differential expression analysis identified differentially expressed CCRGs (DE-CCRGs). These genes were screened by overlapping differentially expressed genes (DEGs) between AML and control groups with CCRGs. Subsequently, functional enrichment analysis and the construction of a protein-protein interaction (PPI) network were conducted to explore the functions of the DE-CCRGs. Univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses identified relevant prognostic genes and developed a prognostic model. Survival analysis of the prognostic gene was performed, followed by functional similarity analysis, immune analysis, enrichment analysis, and drug prediction analysis.

Results: Differential expression analysis revealed 6,743 DEGs, of which 29 DE-CCRGs were selected for this study. Functional enrichment analysis indicated that DE-CCRGs were primarily involved in chemotactic cytokine-related functions and pathways. Six prognostic genes (CXCR3, CXCR2, CXCR6, CCL20, CCL4, and CCR2) were identified and incorporated into the risk model. The model's performance was validated using the GSE12417 dataset. Survival analysis showed significant differences in AML overall survival (OS) between prognostic gene high and low expression groups, indicating that prognostic gene might be significantly associated with patient survival. Additionally, nine different immune cells were identified between the two risk groups. Correlation analysis revealed that CCR2 had the most significant positive correlation with monocytes and the most significant negative correlation with resting mast cells. The tumor immune dysfunction and exclusion score was lower in the high-risk group.

Conclusion: CXCR3, CXCR2, CXCR6, CCL20, CCL4, and CCR2 were identified as prognostic genes correlated to AML and the tumor immune microenvironment. These findings offerred novel insights into the prevention and treatment of AML.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11318587PMC
http://dx.doi.org/10.7717/peerj.17862DOI Listing

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