Table_3_Prognosis and Characterization of Immune Microenvironment in Acute Myeloid Leukemia Through Identification of an Autophagy-Related Signature.xls

Acute myeloid leukemia (AML) is one of the most common hematopoietic malignancies that has an unfavorable outcome and a high rate of relapse. Autophagy plays a vital role in the development of and therapeutic responses to leukemia. This study identifies a potential autophagy-related signature to monitor the prognoses of patients of AML. Transcriptomic profiles of AML patients (GSE37642) with the relevant clinical information were downloaded from Gene Expression Omnibus (GEO) as the training set while TCGA-AML and GSE12417 were used as validation cohorts. Univariate regression analyses and multivariate stepwise Cox regression analysis were respectively applied to identify the autophagy-related signature. The univariate Cox regression analysis identified 32 autophagy-related genes (ARGs) that were significantly associated with the overall survival (OS) of the patients, and were mainly rich in signaling pathways for autophagy, p53, AMPK, and TNF. A prognostic signature that comprised eight ARGs (BAG3, CALCOCO2, CAMKK2, CANX, DAPK1, P4HB, TSC2, and ULK1) and had good predictive capacity was established by LASSO–Cox stepwise regression analysis. High-risk patients were found to have significantly shorter OS than patients in low-risk group. The signature can be used as an independent prognostic predictor after adjusting for clinicopathological parameters, and was validated on two external AML sets. Differentially expressed genes analyzed in two groups were involved in inflammatory and immune signaling pathways. An analysis of tumor-infiltrating immune cells confirmed that high-risk patients had a strong immunosuppressive microenvironment. Potential druggable OS-related ARGs were then investigated through protein–drug interactions. This study provides a systematic analysis of ARGs and develops an OS-related prognostic predictor for AML patients. Further work is needed to verify its clinical utility and identify the underlying molecular mechanisms in AML.

急性髓系白血病（Acute myeloid leukemia, AML）是最常见的造血系统恶性肿瘤之一，预后不良且复发率较高。自噬（autophagy）在白血病发生发展及治疗应答中发挥至关重要的作用。本研究筛选出一种潜在的自噬相关基因特征，用于监测急性髓系白血病患者的预后。本研究从基因表达综合数据库（Gene Expression Omnibus, GEO）下载了携带完整临床信息的急性髓系白血病患者转录组谱（数据集编号GSE37642）作为训练集，并以TCGA-AML队列与GSE12417数据集作为验证队列。分别采用单因素回归分析与多因素逐步Cox回归分析筛选自噬相关特征基因：单因素Cox回归分析共鉴定出32个与患者总生存期（overall survival, OS）显著相关的自噬相关基因（autophagy-related genes, ARGs），这些基因主要富集于自噬、p53、AMPK及TNF信号通路。通过LASSO-Cox逐步回归分析，本研究构建了包含8个自噬相关基因（BAG3、CALCOCO2、CAMKK2、CANX、DAPK1、P4HB、TSC2及ULK1）的预后特征模型，该模型具备良好的预测效能。分析显示，高风险组患者的总生存期显著短于低风险组。该预后特征在校正临床病理参数后仍可作为独立预后预测因子，并在两个外部急性髓系白血病数据集中得到验证。对两组差异表达基因的分析显示，其主要参与炎症与免疫信号通路。肿瘤浸润免疫细胞分析证实，高风险组患者体内存在较强的免疫抑制微环境。随后通过蛋白质-药物相互作用分析，本研究筛选出了与总生存期相关的潜在可靶向自噬相关基因。本研究系统分析了自噬相关基因，并构建了一款与总生存期相关的急性髓系白血病患者预后预测模型。未来仍需开展进一步研究以验证其临床应用价值，并阐明其在急性髓系白血病中潜在的分子机制。