Sun Xiao-Hong, Wan Shun, Chai Yi-Hong, Bai Xiao-Teng, Li Hong-Xing, Xi Ya-Ming
The First Clinical Medical College of Lanzhou University, Lanzhou, China.
The Second Clinical Medical College of Lanzhou University, Lanzhou, China.
Transl Cancer Res. 2023 Jun 30;12(6):1535-1551. doi: 10.21037/tcr-22-2500. Epub 2023 May 29.
Acute myeloid leukemia (AML) is one of the most common hematologic malignancies with a poor prognosis and high recurrence rate. The discovery of new predictive models and therapeutic agents plays a crucial role.
The differentially expressed gene that was explicitly highly expressed in The Cancer Genome Atlas (TCGA) and GSE9476 transcriptome databases were screened and included in the least absolute shrinkage and selection operator (LASSO) regression model to derive risk coefficients and build a risk score model. Functional enrichment analysis was conducted on the screened hub genes to explore the potential mechanisms. Subsequently, critical genes were incorporated into a nomogram model based on risk scores to analyze prognostic value. Finally, this study combined network pharmacology to find potential natural compounds for hub genes and used molecular docking to verify the binding ability of molecular structures to natural compounds to explore drug development for possible efficacy in AML.
A total of 33 highly expressed genes may be associated with poor prognosis of AML patients. After LASSO and multivariate Cox regression analysis of 33 critical genes, Rho-related BTB domain containing 2 (), phospholipase A2 (), interleukin-2 receptor-α (), cysteine and glycine-rich protein 1 (), and olfactomedin-like 2A () were found to played a significant role in the prognosis of AML patients. and were independent prognostic factors of AML. The predictive power of these 5 hub genes in combination with clinical features was better than clinical data alone in predicting AML in the column line graphs and had better predictive value at 1, 3, and 5 years. Finally, through network pharmacology and molecular docking, this study found that diosgenin in Guadi docked well with , beta-sitosterol in Fangji docked well with , and docked well with 3,4-di-O-caffeoylquinic acid in Beiliujinu.
The predictive model of , , , , and combined with clinical features can better guide the prognosis of AML. In addition, the stable docking of , , and with natural compounds may provide new options for treating AML.
急性髓系白血病（AML）是最常见的血液系统恶性肿瘤之一，预后较差且复发率高。发现新的预测模型和治疗药物起着至关重要的作用。
筛选在癌症基因组图谱（TCGA）和GSE9476转录组数据库中明显高表达的差异表达基因，并纳入最小绝对收缩和选择算子（LASSO）回归模型，以得出风险系数并构建风险评分模型。对筛选出的核心基因进行功能富集分析，以探索潜在机制。随后，将关键基因纳入基于风险评分的列线图模型，以分析预后价值。最后，本研究结合网络药理学寻找核心基因的潜在天然化合物，并使用分子对接验证分子结构与天然化合物的结合能力，以探索可能对AML有效的药物开发。
共有33个高表达基因可能与AML患者的不良预后相关。对33个关键基因进行LASSO和多变量Cox回归分析后，发现含Rho相关BTB结构域2（）、磷脂酶A2（）、白细胞介素-2受体-α（）、富含半胱氨酸和甘氨酸蛋白1（）以及嗅觉介质样2A（）在AML患者的预后中起重要作用。和是AML的独立预后因素。这5个核心基因与临床特征相结合在预测AML方面的预测能力在列线图中优于单独的临床数据，并且在1年、3年和5年时具有更好的预测价值。最后，通过网络药理学和分子对接，本研究发现瓜蒂中的薯蓣皂苷元与结合良好，防己中的β-谷甾醇与结合良好，北刘寄奴中的3,4-二-O-咖啡酰奎宁酸与结合良好。
、、、、与临床特征相结合的预测模型可以更好地指导AML的预后。此外，、和与天然化合物的稳定对接可能为治疗AML提供新的选择。
