Jiang Huihui, Liang Li, Liu Tingting, Zhao Zhe, Wang Nana, Wang Jingtao, Hu Yuanyuan, Wang Dongmei, Ye Jingjing, Lu Fei, Ji Chunyan
Department of Hematology, Qilu Hospital of Shandong University, Jinan, 250012, China.
Institute of Software, Chinese Academy of Sciences, Beijing, 100190, China.
Clin Exp Med. 2025 Aug 25;25(1):303. doi: 10.1007/s10238-025-01670-7.
Acute myeloid leukemia is a highly heterogeneous hematopoietic malignancy, and we constructed a prognostic signature combining disulfidptosis-related genes and ferroptosis-related genes to predict the prognosis, immunotherapy response, and drug sensitivity of acute myeloid leukemia (AML) patients. The TCGA-LAML datasets underwent random partitioning into training and validation sets. Subsequently, a prognostic risk signature was formulated using the least absolute shrinkage and selection operator algorithm. Kaplan-Meier survival analysis and receiver operating characteristic curve analysis were employed to assess the clinical significance of the signature. The results of the immune infiltration difference analyses are displayed, and the drug sensitivity analyses were used to identify potentially effective drugs for AML patients. qPCR was employed to validate the expression levels of the signature genes and compared the signature with existing signatures and mutated genes. Univariate and multivariate Cox regression analyses have underscored the signature as an autonomous prognostic risk determinant. Scrutiny into immune infiltration has unveiled significant associations: the risk score exhibits a favorable correlation with monocyte and M2 macrophage counts but an adverse correlation with resting mast cell counts. The expression patterns of immune checkpoint genes diverge between the distinct risk cohorts. Patients categorized as high-risk demonstrate enhanced benefits from cyclopamine, 443654, and 770041, whereas those classified as low-risk exhibit more pronounced advantages from cytarabine and AZD6244. The risk signature demonstrates superior prognostic accuracy compared to established signatures and mutated genes. In summary, our study may provide potential prognostic biomarkers and individualized precision therapy for AML patients.
急性髓系白血病是一种高度异质性的造血系统恶性肿瘤，我们构建了一个结合铁死亡相关基因和二硫化物诱导细胞死亡相关基因的预后特征，以预测急性髓系白血病（AML）患者的预后、免疫治疗反应和药物敏感性。将TCGA-LAML数据集随机划分为训练集和验证集。随后，使用最小绝对收缩和选择算子算法制定了预后风险特征。采用Kaplan-Meier生存分析和受试者工作特征曲线分析来评估该特征的临床意义。展示了免疫浸润差异分析的结果，并利用药物敏感性分析来确定AML患者可能有效的药物。采用qPCR验证特征基因的表达水平，并将该特征与现有特征和突变基因进行比较。单因素和多因素Cox回归分析强调该特征是一个独立的预后风险决定因素。对免疫浸润的研究揭示了显著的关联：风险评分与单核细胞和M2巨噬细胞计数呈正相关，但与静息肥大细胞计数呈负相关。不同风险队列之间免疫检查点基因的表达模式不同。分类为高危的患者从环杷明、443654和770041中获益更多，而分类为低危的患者从阿糖胞苷和AZD6244中获益更明显。与已建立的特征和突变基因相比，该风险特征显示出更高的预后准确性。总之，我们的研究可能为AML患者提供潜在的预后生物标志物和个体化精准治疗。
