Yao Jun, Tang Yu-Chen, Yi Bin, Yang Jian, Chai Yun, Yin Ni, Zhang Zi-Xiang, Wei Yi-Jun, Li De-Chun, Zhou Jian
Department of General Surgery, the First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215006, China.
Pancreatic Disease Research Centre, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215006, China.
J Cancer. 2021 Mar 31;12(11):3164-3179. doi: 10.7150/jca.48661. eCollection 2021.
Alternative splicing (AS), as an effective and universal mechanism of transcriptional regulation, is involved in the development and progression of cancer. Therefore, systematic analysis of alternative splicing in pancreatic adenocarcinoma (PAAD) is warranted. The corresponding clinical information of the RNA-Seq data and PAAD cohort was downloaded from the TCGA data portal. Then, a java application, SpliceSeq, was used to evaluate the RNA splicing pattern and calculate the splicing percentage index (PSI). Differentially expressed AS events (DEAS) were identified based on PSI values between PAAD cancer samples and normal samples of adjacent tissues. Kaplan-Meier and Cox regression analyses were used to assess the association between DEAS and patient clinical characteristics. Unsupervised cluster analysis used to reveal four clusters with different survival patterns. At the same time, GEO and TCGA combined with GTEx to verify the differential expression of AS gene and splicing factor. After rigorous filtering, a total of 45,313 AS events were identified, 1,546 of which were differentially expressed AS events. Nineteen DEAS were found to be associated with OS with a five-year overall survival rate of 0.946. And the subtype clusters results indicate that there are differences in the nature of individual AS that affect clinical outcomes. Results also identified 15 splicing factors associated with the prognosis of PAAD. And the splicing factors ESRP1 and RBM5 played an important role in the PAAD-associated AS events. The PAAD-associated AS events, splicing networks, and clusters identified in this study are valuable for deciphering the underlying mechanisms of AS in PAAD and may facilitate the establishment of therapeutic goals for further validation.
可变剪接（AS）作为一种有效且普遍的转录调控机制，参与了癌症的发生和发展。因此，有必要对胰腺腺癌（PAAD）中的可变剪接进行系统分析。从TCGA数据门户下载了RNA-Seq数据和PAAD队列的相应临床信息。然后，使用Java应用程序SpliceSeq评估RNA剪接模式并计算剪接百分比指数（PSI）。基于PAAD癌组织样本与相邻组织正常样本之间的PSI值，鉴定出差异表达的AS事件（DEAS）。采用Kaplan-Meier和Cox回归分析来评估DEAS与患者临床特征之间的关联。无监督聚类分析用于揭示具有不同生存模式的四个聚类。同时，结合GEO和TCGA与GTEx来验证AS基因和剪接因子的差异表达。经过严格筛选，共鉴定出45313个AS事件，其中1546个为差异表达的AS事件。发现19个DEAS与总生存期相关，五年总生存率为0.946。并且亚型聚类结果表明，个体AS的性质存在差异，会影响临床结果。结果还确定了15个与PAAD预后相关的剪接因子。剪接因子ESRP1和RBM5在PAAD相关的AS事件中起重要作用。本研究中鉴定出的PAAD相关AS事件、剪接网络和聚类对于解读PAAD中AS的潜在机制具有重要价值，可能有助于建立进一步验证的治疗目标。
