Application of prognostic model of fatty acid metabolismrelated genes in renal cell carcinoma
- VernacularTitle:脂肪酸代谢相关基因预后模型在肾透明细胞癌中的应用
- Author:
Wanli DUAN
1
;
Qian DENG
1
;
Wei REN
1
;
Yongyi CHENG
1
;
Yi SUN
1
Author Information
- Publication Type:Journal Article
- Keywords: renal clear cell carcinoma; prognosis; fatty acid metabolism related genes; TCGA database; Cox proportional regression model
- From: Journal of Xi'an Jiaotong University(Medical Sciences) 2022;43(5):684-690
- CountryChina
- Language:Chinese
- Abstract: 【Objective】 To establish a prognostic model of fatty acid metabolism related genes for predicting the prognosis of renal clear cell carcinoma. 【Methods】 The differentially expressed fatty acid metabolism-related genes in renal clear cell carcinoma samples and normal samples in TCGA database were screened by R language software. The Cox proportional hazard regression model was used to select and establish a multigene prognostic model and the prognostic score was calculated. Patients were divided into high-risk group and low-risk group according to the median prognostic score. Kaplan-Meier survival curve was used to analyze the difference in two groups. The clinical pathological factors and prognostic score factors were included in the Cox regression model to analyze the factors affecting the survival of patients with renal clear cell carcinoma. ROC receiver operating curve analysis was used to evaluate the accuracy of the prognostic prediction model. The prognostic model of fatty acid metabolism-related genes and their correlation with clinical factors were analyzed. GSEA enrichment analysis analyzed the differences of gene sets in risk groups. 【Results】 A total of 4 differential genes (CPT1B, HADH, CYP4A11, and ACADSB) were selected to establish a prognostic model for genes related to fatty acid metabolism in renal cell carcinoma. The prognostic risk score (RS) formula is as follows: RS=0.490×CPT1B-0.428×HADH-0.11 × CYP4A11-0.372 × ACADSB. Kaplan-Meier survival analysis confirmed that the overall survival rate of patients with low-risk prognostic score was significantly higher in patients with overall renal clear cell carcinoma, and the difference was statistically significant (P<0.001). Cox regression analysis showed that the prognostic model of genes related to age and fatty acid metabolism is an independent influencing factor for the prognosis of patients with renal clear cell carcinoma (P<0.01). The 5 years’ AUC of the renal clear cell carcinoma ROC curve of the renal cancer fatty acid metabolism related gene model was 0.802. GSEA analysis showed that the difference of 81 gene sets in the low-risk group was statistically significant (P<0.05). 【Conclusion】 The prognostic model of renal cancer fatty acid metabolism-related genes can be used to predict the prognosis of patients with renal clear cell carcinoma, which is conducive to further guide clinical treatment.
