| Autor: |
Youlong Huili, Shiwen Nie, Liguo Zhang, Anliang Yao, Jian Liu, Yong Wang, Lei Wang, Fenghong Cao |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Frontiers in Genetics, Vol 13 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1664-8021 |
| DOI: |
10.3389/fgene.2022.958547 |
| Popis: |
Background: Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cell carcinoma, accounting for approximately 70% of all RCC cases. Cuproptosis, a novel mechanism of cell death, may be a potential target for intervention in tumor development.Methods: Cuproptosis-related prognostic lncRNAs were identified by co-expression analysis and univariable Cox regression. Five lncRNA profiles were obtained by LASSO regression analysis, and a model with high accuracy was constructed to assess the prognosis of ccRCC patients based on these cuproptosis-related lncRNAs. Survival analysis and time-dependent ROC curves were performed for the α and β groups, and the results confirmed the high accuracy of the model in predicting the prognosis of ccRCC patients. Immunoassay, principal component analysis (PCA), and drug sensitivity analysis were also performed for different risk categories. Finally, we classified ccRCC patients into two different subtypes by consistent class clustering, and performed immune checkpoint activation, tumor microenvironment analysis, PCA, and drug sensitivity analysis for different subtypes.Results: We developed a prognostic model using five cuproptosis-associated lncRNAs, which was found to be highly accurate in predicting ccRCC patients’ prognosis. Immunotherapy may be more beneficial to the hyper-risk category and the C2 subtype.Conclusion: The results of this study confirm that five cuproptosis-associated lncRNAs can be used as potential prognostic markers for ccRCC. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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