Survival-associated alternative splicing signatures in esophageal carcinoma
Survival-associated alternative splicing signatures in esophageal carcinoma
复制标题
食管癌中与生存相关的选择性剪接特征
DOI：
10.1093/carcin/bgy123
复制
发表时间：
2019-01-01
期刊：
影响因子：
4.7
通讯作者：
He, Jie
中科院分区：
文献类型：
--
作者：
Mao, Shuangshuang;Li, Yuan;He, Jie
选择性剪接(AS)是增强转录组和蛋白质组多样性的主要机制，已被广泛证明参与了肿瘤发生的全过程。高通量测序技术和快速积累的临床数据集为系统分析作为变异体的信使RNA与患者临床结果之间的关联提供了机会。在这里，我们比较了食道癌(ESCA)和非肿瘤组织之间的差异剪接作为转录本，使用癌症基因组图谱(TCGA)RNA-SEQ数据集描述了87例食管腺癌(EAC)和79例食管鳞癌(ESCC)患者的全基因组生存相关事件，并通过整合的生物信息学分析构建了预测模型和剪接调控网络。共有1738个基因中的2326个AS事件和1360个基因中的1812个AS事件分别被确定与EAC和ESCC队列中的患者的总生存期(OS)显著相关，包括一些肿瘤形成过程中的重要参与者。每种剪接类型的预测模型在区分食管癌患者预后的优劣方面表现良好，EAC外显子跳跃预测模型和食管鳞癌替代受体位置预测模型的曲线下面积分别达到0.942和0.815。剪接调控网络揭示了生存相关剪接因子和预后AS基因之间有趣的相关性。综上所述，我们基于AS信号建立了食道癌患者的预后模型，并构建了新的剪接相关网络。
Alternative splicing (AS), a major mechanism for the enhancement of transcriptome and proteome diversity, has been widely demonstrated to be involved in the full spectrum of oncogenic processes. High-throughput sequencing technology and the rapid accumulation of clinical data sets have provided an opportunity to systemically analyze the association between messenger RNA AS variants and patient clinical outcomes. Here, we compared differentially spliced AS transcripts between esophageal carcinoma (ESCA) and non-tumor tissues, profiled genome-wide survival-associated AS events in 87 patients with esophageal adenocarcinoma (EAC) and 79 patients with esophageal squamous cell carcinoma (ESCC) using The Cancer Genome Atlas (TCGA) RNA-seq data set, and constructed predictive models as well as splicing regulation networks by integrated bioinformatic analysis. A total of 2326 AS events in 1738 genes and 1812 AS events in 1360 genes were determined to be significantly associated with overall survival (OS) of patients in the EAC and ESCC cohorts, respectively, including some essential participants in the oncogenic process. The predictive model of each splice type performed reasonably well in distinguishing good and poor outcomes of patients with esophageal cancer, and values for the area under curve reached 0.942 and 0.815 in the EAC exon skip predictive model and the ESCC alternate acceptor site predictive model, respectively. The splicing regulation networks revealed an interesting correlation between survival-associated splicing factors and prognostic AS genes. In summary, we created prognostic models for patients with esophageal cancer based on AS signatures and constructed novel splicing correlation networks.