AUTHOR=Zhu HuaXin , Wan Qinsi , Tan Jiacong , Ouyang Hengyang , Pan Xinyi , Li MeiHua , Zhao YeYu
TITLE=A novel prognostic signature of cuproptosis-related genes and the prognostic value of FDX1 in gliomas
JOURNAL=Frontiers in Genetics
VOLUME=13
YEAR=2022
URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.992995
DOI=10.3389/fgene.2022.992995
ISSN=1664-8021
ABSTRACT=Background: Gliomas are the most common malignant tumors of the central nervous system, with extremely bad prognoses. Cuproptosis is a novel form of regulated cell death. The impact of cuproptosis-related genes on glioma development has not been reported.
Methods: The TCGA, GTEx, and CGGA databases were used to retrieve transcriptomic expression data. We employed Cox’s regressions to determine the associations between clinical factors and cuproptosis-related gene expression. Overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) were evaluated using the Kaplan-Meier method. We also used the least absolute shrinkage and selection operator (LASSO) regression technique.
Results: The expression levels of all 10 CRGs varied considerably between glioma tumors and healthy tissues. In glioma patients, the levels of CDKN2A, FDX1, DLD, DLAT, LIAS, LIPT1, and PDHA1 were significantly associated with the OS, disease-specific survival, and progression-free interval. We used LASSO Cox’s regression to create a prognostic model; the risk score was (0.882340) *FDX1 expression + (0.141089) *DLD expression + (–0.333875) *LIAS expression + (0.356469) *LIPT1 expression + (–0.123851) *PDHA1 expression. A high-risk score/signature was associated with poor OS (hazard ratio = 3.50, 95% confidence interval 2, –4.55, log-rank p < 0.001). Cox’s regression revealed that the FDX1 level independently predicted prognosis; FDX1 may control immune cell infiltration of the tumor microenvironment.
Conclusion: The CRG signature may be prognostic in glioma patients, and the FDX1 level may independently predict glioma prognosis. These data may afford new insights into treatment.