Department of Pediatrics, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei Province, China.
Department of Plastic Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei Province, China.
Blood Cells Mol Dis. 2019 Jul;77:43-50. doi: 10.1016/j.bcmd.2019.03.008. Epub 2019 Mar 28.
This study aimed to identify critical prognostic molecular markers in Childhood acute myeloid leukemia (AML) and construct nomogram-based model for prognostic prediction. The RNA-sequencing profiles and corresponding clinical information were downloaded from TCGA database. Differential expressed genes (DEG) were screened using limma package, subsequently following by GO and KEGG pathway analysis. Univariate and multivariate cox regression analysis were performed to screen critical DEGs. Nomogram-based prediction model were constructed to identify clinical factors with independent prognostic values, and the accuracy of this model was validated. A total of 214 DEGs were identified from relapse AML samples compared with non-relapse samples. These DEGs were mainly involved in twenty GO terms and three signaling pathways, such as chromatin assembly or disassembly, cytokine-cytokine receptor interaction, and JAK-STAT signaling pathway. Among these genes, Univariate and multivariate cox regression analysis results showed that relapse and risk score were significantly correlated with survival outcomes. Finally, the accuracy ability of nomogram-based prediction model was validated. These six DEGs (ABCA5, CYP7A1, HERC5, etc.) play major roles in AMLs progression. Our nomogram-based prognostic predictive model might be an effective method to estimate survival probability of AML patients with different risk status.
本研究旨在鉴定儿童急性髓系白血病（AML）中的关键预后分子标志物，并构建基于列线图的预后预测模型。从 TCGA 数据库下载 RNA-seq 图谱和相应的临床信息。使用 limma 包筛选差异表达基因（DEG），随后进行 GO 和 KEGG 通路分析。进行单因素和多因素 cox 回归分析以筛选关键的 DEG。构建基于列线图的预测模型，以确定具有独立预后价值的临床因素，并验证该模型的准确性。与非复发样本相比，从复发 AML 样本中鉴定出 214 个 DEG。这些 DEG 主要涉及二十个 GO 术语和三个信号通路，如染色质组装或拆卸、细胞因子-细胞因子受体相互作用和 JAK-STAT 信号通路。在这些基因中，单因素和多因素 cox 回归分析结果表明，复发和风险评分与生存结局显著相关。最后，验证了基于列线图的预测模型的准确性。这些六个 DEG（ABCA5、CYP7A1、HERC5 等）在 AML 进展中起主要作用。我们的基于列线图的预后预测模型可能是评估不同风险状态 AML 患者生存概率的有效方法。
