As suggested by an increasing amount of evidence, there is alternative splicing (AS) modification within malignancy, which is related to cancer occurrence and development. AS within acute myeloid leukemia (AML) has not yet been systematically analyzed yet. This study analyzed the transcriptomic profiling and corresponding clinical data from AML cases based on The Cancer Genome Atlas (TCGA). In addition, the prediction model, along with the splicing network, was used to analyze the prognosis for AML patients according to the seven different AS event types. Among the 34,984 AS events across the 8830 genes, 2896 AS events were detected among 1905 genes, showing marked correlation with the overall survival of patients. The risk scoring model based on all AS event types was the most efficient in identifying the prognosis for AML patients. Meanwhile, the area under the curve at 1-, 3-, 5-year were 0.852, 0.935, 0.955, respectively. At the same time, the splicing regulating network, which was constituted by 21 splicing factor genes as well as 32 AS events related to survival, was characterized. In conclusion, our predictive model constructed based on the AS events accurately predicts the survival for AML patients. In addition, the network between AS events and splicing factor is established, which may serve as a potential mechanism.

中文翻译：

---

选择性剪接事件对急性髓性白血病的影响。

正如越来越多的证据表明的那样，恶性肿瘤内存在其他剪接（AS）修饰，与癌症的发生和发展有关。尚未对急性髓细胞性白血病（AML）中的AS进行系统分析。这项研究基于癌症基因组图谱（TCGA）分析了AML病例的转录组谱和相应的临床数据。此外，根据七种不同的AS事件类型，使用预测模型和剪接网络来分析AML患者的预后。在8830个基因的34,984个AS事件中，在1905个基因中检测到了2896个AS事件，显示与患者的总体生存率显着相关。基于所有AS事件类型的风险评分模型在确定AML患者的预后方面最有效。与此同时，在1年，3年，5年时曲线下的面积分别为0.852、0.935和0.955。同时，表征了由21个剪接因子基因和32个与生存有关的AS事件构成的剪接调节网络。总之，我们基于AS事件构建的预测模型可以准确预测AML患者的生存率。另外，建立了AS事件和剪接因子之间的网络，这可能是一种潜在的机制。