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Analysis of Ferroptosis-Related Gene Expression and Prognostic Factors of Renal Clear Cell Carcinoma Based on TCGA Database

INTRODUCTION: Renal clear cell carcinoma (ccRCC) is a common tumor of the urinary system, most of which are primary malignant tumors with high metastatic rate and remaining incurable. Ferroptosis is a newly discovered form of iron-dependent programmed cell necrosis in recent years, which is inextric...

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Detalles Bibliográficos
Autores principales: Ma, Sijia, Zhao, Mingming, Fan, Jiao, Chang, Meiying, Pan, Zhiyu, Zhang, Ziyan, Xue, Shunxuan, Li, Qi, Zhang, Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8473851/
https://www.ncbi.nlm.nih.gov/pubmed/34588801
http://dx.doi.org/10.2147/IJGM.S323511
Descripción
Sumario:INTRODUCTION: Renal clear cell carcinoma (ccRCC) is a common tumor of the urinary system, most of which are primary malignant tumors with high metastatic rate and remaining incurable. Ferroptosis is a newly discovered form of iron-dependent programmed cell necrosis in recent years, which is inextricably linked to the occurrence and development of tumors progression. Due to the complexity of the interaction between genes in ccRCC, the research on the pathogenesis of ccRCC is still not remarkably accurate. Therefore, whether ferroptosis-related genes (FRGs) can play a role in predicting prognosis in ccRCC needs to be discussed. METHODS: We entered the Cancer Genome Mapping Project (TCGA) database and downloaded the relevant genes and clinical research data of ccRCC patients. Lasso Cox regression was used to construct a multi-gene prognostic model in the TCGA cohort. R language software was used for drawing pictures related to our study. RESULTS: Most of the genes involved in ferroptosis (86.2%) existing differences between the tumor and normal tissues in the TCGA public gene database. In terms of univariate Cox regression analysis, 20 differentially expressed genes (DEGs) were associated with prognosis and survival (P<0.05). A prognostic model of 12 FRGs was constructed, and patients were segmented into two different groups depending on how risky they are. Considering overall survival, the high-risk group is dramatically lower than the low-risk group (P<0.001). In multivariate Cox regression analysis, risk scores and stage turned out be an independent prognostic factor (P<0.001). GO and KEGG analysis and ssGSEA analysis of DEGs revealed that these genes were related to immune-related pathways (P<0.05). CONCLUSION: This study established and identified the changes in FRGs expression and prognostic factors of ccRCC, which can be helpful for prognosis evaluation and clinical treatment of this disease.