利用生物信息学分析开发luminal型乳腺癌自噬相关基因预后模型

Development of a prognostic model of autophagy-related genes in luminal breast cancers using bioinformatics analysis

目的建立基于大规模自噬相关基因的luminal型乳腺癌预后预测模型。方法利用TCGA数据库乳腺癌数据,分别筛选luminal型与非luminal型乳腺癌、癌旁组织中差异表达的自噬相关基因。单因素和多因素Cox回归建立luminal型乳腺癌自噬相关基因预后模型。Kaplan-Meier曲线和生存依赖的受试者工作特征曲线评估预后模型的准确性。结果基于差异表达自噬相关基因,建立了一个3基因(BAG1、CD46、DIRAS3)预后模型预测luminal型乳腺癌患者总生存期。3年、5年和10年的曲线下面积分别为0.708、0.752和0.837。结论 3基因预后模型可以有效预测luminal型乳腺癌患者预后,或许今后可为luminal型乳腺癌的临床治疗提供决策依据。

Objective To establish a prognostic model for luminal breast cancer based on large-scale autophagy-related genes.Methods We identified the differentially expressed autophagy-related genes among luminal and non-luminal breast cancers,cancer-adjacent tissues using breast cancer cohort from TCGA database,respectively.Subsequently,univariate and multivariate Cox regression were used to establish a prognostic model for luminal breast cancers based on differentially expressed autophagy-related genes.The accuracy of the prognostic model was evaluated with Kaplan-Meier curve and survival-dependent receiver operating characteristic(ROC)curves.Results 31 differentially expressed autophagy-related genes in luminal breast cancers were identified.A three-gene(BAG1,CD46,DIRAS3)prognostic model was established to predict the overall survival(OS)of patients with luminal breast cancer.Furthermore,the area under the curve(AUC)at 3-,5-and 10-years were 0.708,0.752 and 0.837,respectively.Conclusion The three-gene prognostic model can effectively predict the prognosis of patients with luminal breast cancer,and may provide decision-making basis for clinical treatment of luminal breast cancers in the future.