整合网络分析构建胃癌自噬相关预后模型

A prognostic model for gastric cancer autophagy based on integrated network analysis

目的本研究旨在构建一种基于自噬基因的预后模型。方法5个独立公共队列中的1,099例胃癌患者的转录组数据纳入研究,整合分析间充质特征和自噬标志基因,构建自噬相关的胃癌预后标志(APSGC)。结果鉴定出5个主调控间充质样亚型分子特征的自噬基因(CCL2、SPHK1、ITGFB1、PEA15、DLC1),基于这5个标志基因,作者构建了APSGC预后模型。在训练和验证数据集中,该模型可将胃癌患者分为高危组和低危组,两组患者在总体生存期(OS)和无复发生存期(RFS)方面均存在显著差异。此外,多变量分析结果表明,APSGC具有较强的独立预后预测效能。基因集富集分析发现,高危组富集表达间充质亚型相关通路。结论通过整合分析构建了一种可靠的自噬相关预后标志。基于此模型的风险分层,有助于指导胃癌患者的精准治疗。

Objective To develop a prognosis signature based on autophagy genes by integrating molecular modalities involved in the mesenchymal subtype.Methods The gene expression profiles of 5 public datasets were applied to this study,including 1,099 gastric cancer patients.Mesenchymal modalities and autophagy signatures were integrated to develop an autophagy-based prognostic signature for gastric cancer(APSGC).Results We identified five autophagy genes as key factors in the mesenchymal subtype and established the APSGC based on these five genes.In the training and 4 validation data sets,the APSGC could divide gastric cancer patients into the high-risk groups and the low-risk groups.There were significant differences in terms of overall survival(OS)and recurrence-free survival(RFS)between the two groups.In addition,the APSGC remained an independent prognostic predictor in multivariate analysis.Furthermore,GSEA results revealed that many mesenchymal related pathways were significantly enriched in high-risk group.Conclusion We propose a promising autophagy-based prognostic signature by integrating network analysis,which can be used for risk stratification and guiding the precision treatment of gastric cancer patients.