Liang Ying, Song Jukun, He Dengqi, Xia Yu, Wu Yadong, Yin Xinhai, Liu Jianguo
Department of Orthodontics, Guiyang Hospital of Stomatology, Medical College, Guiyang, China.
Guiyang Stomatological Hospital Affiliated to Zunyi Medical University, Guizhou, China.
J Cell Physiol. 2019 Sep;234(9):15836-15846. doi: 10.1002/jcp.28241. Epub 2019 Feb 10.
Previous studies have shown that alternative splicing (AS) plays a key role in carcinogenesis and prognosis of cancer. However, systematic profiles of AS signatures in head and neck cancer (HNC) have not yet been reported.
In this study, AS data, RNA-Seq data, and corresponding clinicopathological information of 489 HNC patients were downloaded from The Cancer Genome Atlas. Univariate and multivariate Cox regression analyses were performed to screen for survival-associated AS events. Functional and pathway enrichment analysis was also performed. The prognostic models and splicing networks were constructed using integrated bioinformatics analysis tools.
Among the 42,849 alternating splicing events identified in 10,121 genes, 5,165 survival-associated AS events in 2,419 genes were observed in univariate Cox regression analysis. Among the seven types, alternate terminator events were the most powerful prognostic factors. Multivariate Cox analysis was then used to screen for the AS genes with prognostic value. Four candidate genes (TPM1, CLASRP, PRRC1, and DNASE1L1) were found to be independent prognostic factors for HNC patients. A prognostic prediction model was built based on the four genes. The area under the receiver operating characteristic risk score curve for predicting the survival status of HNC patients was 0.704. In addition, splicing interaction network indicated that the splicing factors have significant functions in HNC.
A comprehensive analysis of AS events in HNC was performed. A powerful prognostic predictor for HNC patients was established based on AS events could.
先前的研究表明,可变剪接(AS)在癌症的发生和预后中起关键作用。然而,头颈部癌(HNC)中AS特征的系统概况尚未见报道。
在本研究中,从癌症基因组图谱下载了489例HNC患者的AS数据、RNA测序数据及相应的临床病理信息。进行单因素和多因素Cox回归分析以筛选与生存相关的AS事件。还进行了功能和通路富集分析。使用综合生物信息学分析工具构建预后模型和剪接网络。
在10121个基因中鉴定出的42849个可变剪接事件中,单因素Cox回归分析观察到2419个基因中的5165个与生存相关的AS事件。在这七种类型中,可变终止子事件是最有力的预后因素。然后使用多因素Cox分析筛选具有预后价值的AS基因。发现四个候选基因(TPM1、CLASRP、PRRC1和DNASE1L1)是HNC患者的独立预后因素。基于这四个基因建立了预后预测模型。预测HNC患者生存状态的受试者工作特征风险评分曲线下面积为0.704。此外,剪接相互作用网络表明剪接因子在HNC中具有重要功能。
对头颈部癌中的AS事件进行了全面分析。基于AS事件建立了一种强大的HNC患者预后预测指标。