12个铁代谢相关基因的多元回归模型可预测乳腺癌的发展

A multivariate regression model of 12 genes associated with iron metabolism predicted the development of breast cancer

目的探讨铁代谢相关基因(IRGs)的异常表达与乳腺癌的发生发展的关系,寻找相关基因构建分子标记以预测乳腺癌的发生发展。方法通过GSEA数据库发现与铁代谢相关的基因本体(GO)通路。在这些GO富集分析通路中有367个与铁代谢相关的基因,然后从肿瘤基因组图谱(TCGA)获得乳腺癌的RNA数据和临床数据,通过差异基因的数据分析,发现与乳腺癌特异性相关的铁代谢基因,然后对这些基因进行统计筛选后构建多元回归差异模型。结果由ATP6AP1、ABAT、TTYH1、AIFM3、P4HA3、CCNB1、TFRC、CH25H、CYP46A1、BRIP1、ATP6V0B、SLC11A1铁代谢基因构建的模型可预测乳腺癌的发生和发展,其中高危组的存活率明显低于低危组[(21.5%比37.5%),生存分析(Kaplan-Meier),P<0.01]。ROC曲线用于验证1、3、5、10年的预测准确性高[1年曲线下面积(AUC)=0.673,3年AUC=0.704,5年AUC=0.629,10年AUC=0.701]。结论铁代谢相关基因可预测乳腺癌的发生发展。

Objective To investigate the relationship between abnormal expression of iron metabolism-related genes(IRGs)and the occurrence and development of breast cancer and find out molecular markers for related genes to predict the occurrence and progression of breast cancer.Methods In order to further explore the predictive role of IRGs in breast cancer,RNA data and clinical data of breast cancer were obtained from the cancer genome atlas(TCGA),and then iron metabolism-related pathways were obtained from the GSEA database to find iron metabolism genes specifically related to breast cancer,and then a multi-regression difference model was constructed after statistical screening of these genes.Results Models constructed from ATP6AP1,ABAT,TTYH1,AIFM3,P4HA3,CCNB1,TFRC,CH25H,CYP46A1,BRIP1,ATP6V0B,SLC11A1 iron metabolism genes could be well used to predict the occurrence and development of breast cancer.The survival rate of the high-risk group was significantly lower than that of the low-risk group[(21.5%vs.37.5%),survival analysis(Kaplan-Meier),P<0.01].The ROC curves were used to verify high prediction accuracy at 1,3,5 and 10 years[1-year area under curve(AUC)=0.673,3-year AUC=0.704,5-year AUC=0.629,10-year AUC=0.701].Conclusion Iron metabolism-related genes can predict the development and progression of breast cancer.