医学
单变量
前列腺癌
比例危险模型
预测模型
肿瘤科
腺癌
内科学
单变量分析
生存分析
计算生物学
多元分析
总体生存率
癌症
多元统计
统计
生物
数学
作者
Song Ouyang,Jihong Liu,Qinzhang Wang
标识
DOI:10.2217/bmm-2020-0095
摘要
Aim: To study the expression patterns and prognostic value of the m6A-associated regulators in prostate adenocarcinoma (PRAD). Materials & methods: The mRNA expression and clinical data were downloaded from ‘The Cancer Genome Atlas database’. The m6A-associated variants were downloaded from m6AVar database, and combined with 14 common m6A regulators for subsequent analysis. One-way analysis of variance, univariate Cox regression analysis and least absolute shrinkage and selection operator algorithm were successively applied to obtain the ultimate regulators and prognostic model. Finally, consensus clustering, protein–protein interaction (PPI) and enrichment analysis were performed. Result: Nine regulators were obtained. PRAD patients could be classified into two risk groups and subclasses with significant survival differences by the prognostic model and consensus clustering, respectively. Conclusion: All these nine regulators were related to prognosis in PRAD, and could be used as clinical biomarkers.
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