CELL INTELLIGENCE · 肿瘤细胞治疗研究

Acute myeloid leukemia (AML) is a hematological malignancy characterized by complex immune microenvironment. This study aims to identify immune-related prognostic biomarkers in AML.

Multiple public sequencing datasets were utilized to analyze differentially expressed genes (DEGs) in AML. Single-sample gene set enrichment analysis (ssGSEA) and weighted gene co-expression network analysis (WGCNA) were also performed. Immune cell infiltration was assessed at the single-cell level. NKT cell marker genes were intersected with the most AML-relevant module genes to identify key genes. Prognostic genes were screened using the Cox Lasso regression model, and their prognostic value was evaluated with Cox random forest and Kaplan-Meier survival analyses. Gene expression was validated using RT-qPCR and Western blot, and immune cell levels were analyzed by flow cytometry.

A total of 1,919 common DEGs were obtained between AML and controls. WGCNA revealed that the brown module was most strongly associated with AML. Single-cell analysis showed that NKT cell infiltration was significantly reduced in AML patients, consistent with ssGSEA results. Forty intersecting genes were identified between NKT cell marker genes and brown module genes. Cox Lasso regression identified 10 prognostic genes (FGFBP2, GZMB, GZMH, IKZF3, IL2RB, KLRB1, KLRC2, RHOF, RUNX3, and STAT4). A risk score model based on these genes stratified AML patients into high-risk and low-risk groups, with significant differences in survival prognosis between the two groups. RT-qPCR and Western blot analyses showed that these genes were significantly downregulated in AML patients. Flow cytometry results revealed significantly lower levels of NKT and CD8 + T cells in AML patients compared to controls.

This study identified key prognostic genes in AML and highlighted the critical role of NKT cells in AML pathogenesis. The study provides new insights and potential biomarkers for understanding AML biology, prognosis, and therapeutic targets.