自然杀伤T细胞相关基因在急性髓性白血病中的预后价值。

IF 5.3 2区 医学 Q1 ONCOLOGY
Qiong Liu, Zhaona Zhou, Ping Xu, Shuoye Li, Xiuli Bu, Jian Zhang, Jun Guo
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引用次数: 0

摘要

背景:急性髓系白血病(AML)是一种以复杂免疫微环境为特征的血液系统恶性肿瘤。本研究旨在确定AML中与免疫相关的预后生物标志物。方法:利用多个公共测序数据集分析AML中的差异表达基因(DEGs)。同时进行单样本基因集富集分析(ssGSEA)和加权基因共表达网络分析(WGCNA)。免疫细胞浸润在单细胞水平进行评估。将NKT细胞标记基因与aml相关最多的模块基因交叉,鉴定关键基因。采用Cox Lasso回归模型筛选预后基因,采用Cox随机森林和Kaplan-Meier生存分析评估其预后价值。采用RT-qPCR和Western blot验证基因表达,流式细胞术分析免疫细胞水平。结果:在AML和对照组之间共获得1,919个共同deg。WGCNA显示棕色模块与AML的相关性最强。单细胞分析显示,AML患者的NKT细胞浸润明显减少,与ssGSEA结果一致。在NKT细胞标记基因和棕色模块基因之间鉴定出40个交叉基因。Cox Lasso回归鉴定出10个预后基因(FGFBP2、GZMB、GZMH、IKZF3、IL2RB、KLRB1、KLRC2、RHOF、RUNX3和STAT4)。基于这些基因的风险评分模型将AML患者分为高风险和低风险组,两组患者的生存预后存在显著差异。RT-qPCR和Western blot分析显示,这些基因在AML患者中显著下调。流式细胞术结果显示,与对照组相比,AML患者的NKT和CD8 + T细胞水平显著降低。结论:本研究确定了AML的关键预后基因,强调了NKT细胞在AML发病机制中的关键作用。该研究为了解AML生物学、预后和治疗靶点提供了新的见解和潜在的生物标志物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prognostic value of natural killer T cell related genes in acute myeloid leukemia.

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

Methods: 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.

Results: 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.

Conclusion: 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.

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来源期刊
CiteScore
10.90
自引率
1.70%
发文量
360
审稿时长
1 months
期刊介绍: Cancer Cell International publishes articles on all aspects of cancer cell biology, originating largely from, but not limited to, work using cell culture techniques. The journal focuses on novel cancer studies reporting data from biological experiments performed on cells grown in vitro, in two- or three-dimensional systems, and/or in vivo (animal experiments). These types of experiments have provided crucial data in many fields, from cell proliferation and transformation, to epithelial-mesenchymal interaction, to apoptosis, and host immune response to tumors. Cancer Cell International also considers articles that focus on novel technologies or novel pathways in molecular analysis and on epidemiological studies that may affect patient care, as well as articles reporting translational cancer research studies where in vitro discoveries are bridged to the clinic. As such, the journal is interested in laboratory and animal studies reporting on novel biomarkers of tumor progression and response to therapy and on their applicability to human cancers.
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