A six-gene prognostic model predicts overall survival in bladder cancer patients
A six-gene prognostic model predicts overall survival in bladder cancer patients
复制标题
六基因预后模型预测膀胱癌患者的总生存期。
DOI：
10.1186/s12935-019-0950-7
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发表时间：
2019-09-05
影响因子：
5.8
通讯作者：
Chen, Zhiwen
中科院分区：
文献类型：
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作者：
Wang, Liwei;Shi, Jiazhong;Chen, Zhiwen
背景膀胱癌（BC）的病死率和复发率逐渐增加。DNA甲基化是BC发病机制中与基因转录相关的重要调节因子。我们描述了一个全面的表观遗传学研究进行分析DNA甲基化驱动的基因在BC。方法从美国癌症基因组图谱（TCGA）中下载有关乳腺癌患者DNA甲基化、基因转录组和生存率的数据。MethylMix用于检测BC特异性高/低甲基化基因。使用Metascape进行基因本体（GO）富集和京都基因和基因组百科全书（KEGG）途径分析。进行最小绝对收缩和选择算子（LASSO）-惩罚的考克斯回归以鉴定特征维数降低并区分水肿相关甲基化驱动的基因。随后，我们开发了一个六基因风险评估模型和一个新的肿瘤相关诺模图来预测总生存期（OS）。进行生存分析，以探讨这六个基因的个体预后意义。结果共鉴定出167个甲基化驱动基因。基于LASSO考克斯回归，6个基因，即，选择ARHGDIB、LINC 00526、IDH 2、ARL 14、GSTM 2和LURAP 1用于开发风险评价模型。Kaplan-Meier曲线表明低风险组患者的OS明显更好（P = 1.679e-05）。在OS 3年时，该模型的曲线下面积（AUC）为0.698。在亚组中进行的验证证明了该模型的有效性。然后，我们设计了一个OS相关的诺模图，其中包括风险评分和临床因素。诺模图的一致性指数为0.694。IDH 2和ARL 14的甲基化水平与生存结果明显相关。此外，甲基化和基因表达匹配的生存分析显示，ARHGDIB和ARL 14可以作为独立的预后指标。在这6个基因中，ARHGDIB的6个甲基化位点、GSTM 2的3个甲基化位点、ARL 14的1个甲基化位点、LINC 00526的2个甲基化位点和LURAP 1的2个甲基化位点与BC预后有意义地相关。此外，几个异常甲基化位点被确定为与基因表达相关。结论发现了生存期较好和较差的BC患者存在差异甲基化，并将6个基因标记与临床特征相结合，提供了一个风险评估模型。
Background The fatality and recurrence rates of bladder cancer (BC) have progressively increased. DNA methylation is an influential regulator associated with gene transcription in the pathogenesis of BC. We describe a comprehensive epigenetic study performed to analyse DNA methylation-driven genes in BC. Methods Data related to DNA methylation, the gene transcriptome and survival in BC were downloaded from The Cancer Genome Atlas (TCGA). MethylMix was used to detect BC-specific hyper-/hypo-methylated genes. Metascape was used to carry out gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. A least absolute shrinkage and selection operator (LASSO)-penalized Cox regression was conducted to identify the characteristic dimension decrease and distinguish prognosis-related methylation-driven genes. Subsequently, we developed a six-gene risk evaluation model and a novel prognosis-related nomogram to predict overall survival (OS). A survival analysis was carried out to explore the individual prognostic significance of the six genes. Results In total, 167 methylation-driven genes were identified. Based on the LASSO Cox regression, six genes, i.e., ARHGDIB, LINC00526, IDH2, ARL14, GSTM2, and LURAP1, were selected for the development of a risk evaluation model. The Kaplan-Meier curve indicated that patients in the low-risk group had considerably better OS (P = 1.679e-05). The area under the curve (AUC) of this model was 0.698 at 3 years of OS. The verification performed in subgroups demonstrated the validity of the model. Then, we designed an OS-associated nomogram that included the risk score and clinical factors. The concordance index of the nomogram was 0.694. The methylation levels of IDH2 and ARL14 were appreciably related to the survival results. In addition, the methylation and gene expression-matched survival analysis revealed that ARHGDIB and ARL14 could be used as independent prognostic indicators. Among the six genes, 6 methylation sites in ARHGDIB, 3 in GSTM2, 1 in ARL14, 2 in LINC00526 and 2 in LURAP1 were meaningfully associated with BC prognosis. In addition, several abnormal methylated sites were identified as linked to gene expression. Conclusion We discovered differential methylation in BC patients with better and worse survival and provided a risk evaluation model by merging six gene markers with clinical characteristics.