1 Shandong Provincial Key Laboratory of Oral Tissue Regeneration, School of Stomatology, Shandong University, Jinan, China.
2 Department of Stomatology, Haiyuan College of Kunming Medical University, Kunming, China.
DNA Cell Biol. 2019 Jul;38(7):627-638. doi: 10.1089/dna.2019.4644. Epub 2019 Apr 26.
Head and neck squamous cell carcinoma (HNSC) is a common malignancy with high mortality and poor prognosis. Alternative splicing (AS) is a transcriptional regulation mechanism that generates multiple transcripts from same genes, and aberrant AS signatures of cancers can be predictive for prognosis. We identified the survival-related AS events and splicing factors (SFs) from the RNA sequencing data and the corresponding clinical information of an HNSC cohort downloaded from The Cancer Genome Atlas (TCGA) and SpliceSeq. The independent prognostic predictors were assessed by Cox proportional regression analysis, and the regulatory network of SFs and AS events was analyzed by Spearman's test and constructed. A total of 4626 survival-related AS events in 3280 genes were identified, and most were protective factors. Among the different types of splicing events, exon skip was the most frequent. The prognostic models were constructed for each type of AS, and the area under the curve of the receiver operating characteristic curve of the combined prognostic model was 0.765, indicating good predictive performance. Finally, a correlation network between SF and AS events was constructed. We identified prognostic predictors based on AS events that stratified HNSC patients into the high- and low-risk groups, and revealed splicing networks that provide insights into the underlying mechanisms.
头颈部鳞状细胞癌（HNSC）是一种常见的恶性肿瘤，死亡率高，预后差。可变剪接（AS）是一种转录调控机制，它能从同一基因产生多个转录本，而癌症的异常 AS 特征可用于预测预后。我们从 HNSC 队列的 RNA 测序数据和从癌症基因组图谱（TCGA）和 SpliceSeq 下载的相应临床信息中鉴定了与生存相关的 AS 事件和剪接因子（SF）。通过 Cox 比例风险回归分析评估独立预后预测因子，并通过 Spearman 检验和构建分析 SF 和 AS 事件的调控网络。在 3280 个基因中鉴定了 4626 个与生存相关的 AS 事件，其中大多数是保护因素。在不同类型的剪接事件中，外显子跳跃最为常见。为每种类型的 AS 构建了预后模型，联合预后模型的受试者工作特征曲线下面积为 0.765，表明具有良好的预测性能。最后，构建了 SF 和 AS 事件之间的相关网络。我们基于 AS 事件确定了预后预测因子，这些预测因子将 HNSC 患者分为高风险和低风险组，并揭示了剪接网络，为潜在机制提供了见解。
