Construction of Prognostic Model for Cuprotosis in Hepatocellular Carcinoma Based on TCGA Database
10.3971/j.issn.1000-8578.2023.22.0875
- VernacularTitle:基于TCGA数据库构建肝癌铜死亡的预后模型
- Author:
Qingsong LEI
1
;
Lin LI
Author Information
1. Department of Radiotherapy Oncology, Chongqing University Cancer Hospital, Chongqing 400030, China
- Publication Type:Research Article
- Keywords:
Cuprotosis;
Hepatocellular carcinoma;
TCGA database;
Prognosis model
- From:
Cancer Research on Prevention and Treatment
2023;50(3):276-282
- CountryChina
- Language:Chinese
-
Abstract:
Objective To construct a prognostic model for cuprotosis-related genes (CRGs) in patients with hepatocellular carcinoma (HCC). Methods Differential expression of CRGs in HCC was analyzed on the basis of datasets from the TCGA database. The potential mechanisms of CRGs and their related genes in HCC were explored through GO and KEGG enrichment analyses. The prognostic value of the CRGs was evaluated through Kaplan-Meier survival analysis, and the relationship between CRG expression and immune cell infiltration was investigated. CRGs significantly correlated with prognosis in patients with HCC were identified. A prognostic model was established through univariate, Lasso regression, and multivariate Cox regression analyses. The patients were divided into two groups by risk score. ROC curve was used in evaluating the prognostic model. The relationship of risk score or clinical factors with prognosis was analyzed through univariate and multivariate Cox regression analyses. Results A total of 11 differentially expressed CRGs in HCC were obtained. The main enriched GO item of CRGs and their related genes was oxidoreductase activity, acting on the aldehyde or oxo group of donors, and the main enriched KEGG pathway was carbon metabolism. The expression of CRGs was significantly correlated with pDC, T helper cells and other immune cells (P < 0.05). Three CRGs (CDKN2A, DLAT, and LIPT1) were screened and a prognostic model was constructed. There was significant difference in overall survival between the high- and low-risk groups (P < 0.001). The risk score is an independent risk factor for poor prognosis (P < 0.001). Conclusion The prognostic model for CRGs in patients with HCC is constructed using TCGA database data. This model may be used in evaluating patient prognosis.
