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首页> 外文期刊>Journal of cellular physiology. >Identification of a prognostic alternative splicing signature in oral squamous cell carcinoma
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Identification of a prognostic alternative splicing signature in oral squamous cell carcinoma

机译：识别一个预后的选择拼接的签名在口腔鳞状细胞癌

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摘要

Alternative splicing (AS) is critically associated with tumorigenesis and patient's prognosis. Here, we systematically analyzed survival-associated AS signatures in oral squamous cell carcinoma (OSCC) and evaluated their prognostic predictive values. Survival-related AS events were identified by univariate and multivariate Cox regression analyses using OSCC data from the TCGA head neck squamous cell carcinoma data set. The Percent Spliced In calculated by SpliceSeq from 0 to 1 was used to quantify seven types of AS events. A predictive model based on AS events was constructed by least absolute shrinkage and selection operator Cox regression assay and further validated using a training-testing cohort design. Patient survival was estimated using the Kaplan-Meier method and compared with Log-rank test. The receiver operating characteristics curve area under the curves was used to evaluate the predictive abilities of these predictive models. Furthermore, gene-gene interaction networks and the splicing factors (SFs)-AS regulatory network was generated by Cytoscape. A total of 825 survival-related AS events within 719 genes were identified in OSCC samples. The integrative predictive model was better at predicting outcomes of patients as compared to those models built with the individual AS event. The predictive model based on three AS-related genes also effectively predicted patients' survival. Moreover, seven survival-related SFs were detected in OSCC including RBM4, HNRNPD, and HNRNPC, which have been linked to tumorigenesis. The SF-AS network revealed a significant correlation between survival-related AS genes and these SFs. Our findings revealed a systemic portrait of survival-associated AS events and the splicing network in OSCC, suggesting that AS events might serve as novel prognostic biomarkers and therapeutic targets for OSCC.
机译：可变剪接(因为)是非常相关的与肿瘤发生和患者的预后。我们系统地分析了survival-associated签名在口腔鳞状细胞癌(OSCC)和评估预后的预测价值。Survival-related事件被确定单变量和多变量Cox回归使用OSCC TCGA头颈的数据分析鳞状细胞癌的数据集。在计算拼接SpliceSeq从0到1被用来量化七种类型的事件。基于事件的预测模型由至少绝对收缩和运营商Cox回归分析和选择进一步验证使用training-testing队列设计。并与Log-rank kaplan meier方法测试。曲线面积曲线是用来评估这些预测的预测能力模型。网络和(SFs)——的连接因素监管网络是由Cytoscape生成。在总共825 survival-related事件719个基因被确定在OSCC样本。综合预测模型是更好的预测结果的病人相比这些模型建立与个人事件。基于三个相关的预测模型基因也有效地预测患者的生存。被发现在OSCC包括RBM4 HNRNPD,HNRNPC,与肿瘤发生有关。SF-AS网络透露一个重要基因和survival-related之间的相关性这些SFs。事件和survival-associated的画像在OSCC拼接网络,说明事件可能成为小说预后的生物标志物和治疗OSCC的目标。

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