目的:建立基于自噬和铁死亡相关基因的预后模型,并基于肾透明细胞癌(ccrCC)的自噬基因(autophagy related genes,ARGs)和铁死亡基因(ferroptosis related genes,FRGs)模型评估预后.方法:通过癌症基因组图谱(TCGA)数据库中的ccRCC 数据集识别与风险相关的ARGs和FRGs,进行功能富集和肿瘤分型分析,通过单变量和多变量Cox回归建立 537 例患者的预后风险模型.多指标ROC用于评估模型的准确性.最后使用GSE29609 数据集验证.结果:共发现37 个差异表达的基因.单变量和多变量Cox回归确定了 8 个与OS 相关的风险相关基因:CASP4、PRKCQ、BNIP3、BAG1、BIRC5、CHAC1、ATG16L2、EIF4EBP1.Kaplan-Meier生存分析显示,高危组患者生存率较低,多指标ROC曲线下面积＞0.75,说明模型预测准确率较高.然后基于CIBERSORT算法进行免疫细胞浸润评估.结论:基于 8 个ARGs和FRGs的肾透明细胞癌相关基因预后模型具有一定的准确性,可更准确地指导临床治疗.
Establishment and verification of a renal clear-cell carcinoma tumor prognosis-model based on autophagy and ferroptosis genes
Objective:To investigate the influence of autophagy-relevant genes(ARGs)and fer-roptosis-related genes(FRGs)on the prognosis of patients with ccRCC(clear cell renal carcinoma),and evaluate the prognosis based on ARGs and FRGs models of ccRCC.Methods:Risk-related ARGs and FRGs were identified in the ccRCC dataset from the TCGA database,and functional enrich-ment analysis and tumor classification were performed.The Cox proportional hazards model of 37 ccRCC patients was established through univariate and multivariate Cox regression.Multi-index ROC curve was used to assess the accuracy of the model.Finally,a GSE29609 dataset was used to verify whether our conclusion is feasible or not.Results:A total of 37 differentially expressed ARGs and FRGs were found.Univariate and multivariate Cox regression identified 8 risk-related genes related to OS,which are CASP4,PRKCQ,BNIP3,BAG1,BIRC5,CHAC1,ATG16L2 and EIF4EBP1.A Kaplan-Meier analysis results showed that patients at high risk of morbidity had lower survivability.The area(performance index)under the ROC curve was＞0.75,indicating that the model's prediction accu-racy was higher.Then the immune cell infiltration were evaluated based on the CIBERSORT algo-rithm.Conclusion:The prognostic model of ccRCC-related genes based on 8 ARGs and FRGs has a certain accuracy and could be used to guide clinical treatment more accurately.
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