Systemic Analysis of RNA Alternative Splicing Signals Related to the Prognosis for Head and Neck Squamous Cell Carcinoma
Systemic Analysis of RNA Alternative Splicing Signals Related to the Prognosis for Head and Neck Squamous Cell Carcinoma
复制标题
与头颈鳞状细胞癌预后相关的 RNA 选择性剪接信号的系统分析
DOI：
10.3389/fonc.2020.00087
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发表时间：
2020-02-07
影响因子：
4.7
通讯作者：
Lv, Yunxia
中科院分区：
文献类型：
--
作者：
Li, Zhexuan;Chen, Xun;Lv, Yunxia
选择性剪接（alternative splicing，AS）是蛋白质多样性产生的重要机制。越来越多的证据表明，失控的AS与肿瘤的发生、发展密切相关。头颈部鳞状细胞癌（HNSCC）全基因组AS的系统分析尚未进行，考虑这一主题仍处于初步阶段，需要进一步调查。本研究对TCGA数据库中555例临床HNSCC样本的全基因组AS事件进行了系统的生物信息学分析。首先，我们统计分析了HNSCC样本中7种AS事件类型的分布。然后通过单因素生存分析，观察AS与疾病预后的关系，发现437个AS事件的交叉点与总生存率显著相关。其中，335个交叉基因在与总生存和复发相关的基因上表现出高度一致性。总生存率与AS事件显著相关。与生存相关的ES事件发生率明显降低，AP和AT事件发生率明显升高。此外，AT事件占比最大。多元回归模型分析证明AS可以成为HNSCC的一种新的分类方法，KEGG富集分析证明与AS事件相互作用的基因和蛋白大多具有不同的生物学功能，与多种疾病相关。最后，通过特征基因的筛选和预后模型的构建，筛选出7个与生存和复发相关的交叉基因，并对这些特征基因进行多变量生存模型分析验证，从而对不同剪接时间和基因表达水平下的预后进行分类。这些结果为我们的进一步研究奠定了坚实的基础，并在显示AS与HNSCC预后的相关性方面发挥了决定性作用。
Alternative splicing (AS) is an important mechanism that is responsible for the production of protein diversity. An increasing body of evidence has suggested that out-of-control AS is closely related to the genesis and development of cancer. Systematic analysis of genome-wide AS in head and neck squamous cell carcinoma (HNSCC) has not yet been carried out, and consideration of this topic remains at the preliminary stage and requires further investigation. In this study, systemic bioinformatic analysis was carried out on the genome-wide AS events of 555 clinical HNSCC samples from the TCGA database. Firstly, we statistically analyzed the distributions of seven AS event types in HNSCC samples. Then, through univariate survival analysis, we observed the relationship between AS and the prognosis of the disease and found that 437 intersections of AS events were significantly related to overall survival. Among them, 335 cross-genes showed a high degree of consistency in the genes associated with overall survival and recurrence. The overall survival was significantly related to AS events. Besides, the frequency of overall survival-related ES events was evidently reduced, while the AP and the AT events were increased. In addition, AT events accounted for the largest proportion. Further, multiple regression model analysis proved that AS could become a new classification method for HNSCC, and KEGG enrichment analysis proved that most genes and proteins interacting with AS events had different biological functions and were associated with a variety of diseases. Finally, through the selection of characteristic HNSCC genes and the construction of a prognostic model, seven cross-genes related to survival and recurrence were screened out, and these characteristic genes were verified by multivariate survival model analysis so as to classify the prognosis at different splicing times and gene expression levels. These results have laid a solid foundation for our further research and play a decisive role in showing the correlation of AS with the prognosis of HNSCC.