基于脂质代谢与内质网应激的肾透明细胞癌免疫浸润及预后预测模型

A lipid metabolism and endoplasmic reticulum stress-based predictive model for immune infiltration and prognosis in clear cell renal cell carcinoma

摘要:

目的 基于脂质代谢与内质网应激相关基因构建肾透明细胞癌（ccRCC）免疫浸润及预后的风险预测模型。方法 下载癌症基因组图谱（TCGA）数据库中ccRCC转录组数据进行差异分析，对差异表达基因（DEGs）与脂质代谢与内质网应激相关基因进行整合，筛选8个预后相关基因（LERGs）。利用最小绝对收宿和选择算子（LASSO）方法进一步筛选出5个基因用于构建预测模型。结果 预测模型具有良好的预测性能，曲线下面积（AUC）为0.7；构建风险评分模型的5个基因的单因素Cox回归显示HSD11B1、CYP21A2、IL6、F2和ADIPOQ均为ccRCC患者预后的危险因素；高风险组患者中死亡事件显著高于低风险患者，Fuhrman分级高肿瘤的比例明显高于低风险组，病理T分期高的比例高于低风险组，而抗肿瘤免疫细胞浸润情况差于低风险组，且高低风险组最化疗药物敏感性存在显著差异（P<0.05）。结论 基于脂质代谢与内质网应激相关基因构建的风险预测模型对ccRCC患者的免疫浸润及预后预测价值较高。

Abstract:

Objective To construct a risk prediction model for immune infiltration and prognosis in clear cell renal cell carcinoma (ccRCC) based on lipid metabolism and endoplasmic reticulum stress-related genes.Methods Transcriptome data of ccRCC from the Cancer Genome Atlas (TCGA) database were downloaded for differential analysis. Differentially expressed genes (DEGs) were integrated with genes related to lipid metabolism and endoplasmic reticulum stress to screen for 8 prognosis-related genes (LERGs). The least absolute shrinkage and selection operator (LASSO) method was used to further screen 5 genes for constructing the prediction model.Results The prediction model demonstrated good predictive performance with an AUC value of 0.7. Univariate Cox regression of the 5 genes in the risk scoring model showed that HSD11B1, CYP21A2, IL6, F2, and ADIPOQ were all risk factors for the prognosis of ccRCC patients. The high-risk group had a significantly higher number of death events than the low-risk group. The proportion of high Fuhrman grade tumors was significantly higher in the high-risk group than in the low-risk group. The proportion of high pathological T-stage was higher in the high-risk group. The anti-tumor immune cell infiltration was poorer in the high-risk group, and there were significant differences in chemotherapy drug sensitivity between the high and low-risk groups, all with statistical significance (P<0.05).Conclusion The risk prediction model based on lipid metabolism and endoplasmic reticulum stress-related genes has high predictive value for immune infiltration and prognosis in ccRCC patients.