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Construction of a ferroptosis-related signature based on seven lncRNAs for prognosis and immune landscape in clear cell renal cell carcinoma

BACKGROUND: Recent studies have demonstrated that long non-coding RNAs (lncRNAs) are involved in regulating tumor cell ferroptosis. However, prognostic signatures based on ferroptosis-related lncRNAs (FRLs) and their relationship to the immune microenvironment have not been comprehensively explored...

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Detalles Bibliográficos
Autores principales: Wei, Shi-Yao, Feng, Bei, Bi, Min, Guo, Hai-Ying, Ning, Shang-Wei, Cui, Rui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758795/
https://www.ncbi.nlm.nih.gov/pubmed/36528763
http://dx.doi.org/10.1186/s12920-022-01418-2
Descripción
Sumario:BACKGROUND: Recent studies have demonstrated that long non-coding RNAs (lncRNAs) are involved in regulating tumor cell ferroptosis. However, prognostic signatures based on ferroptosis-related lncRNAs (FRLs) and their relationship to the immune microenvironment have not been comprehensively explored in clear cell renal cell carcinoma (ccRCC). METHODS: In the present study, the expression profiles of ccRCC were acquired from The Cancer Genome Atlas (TCGA) database; 459 patient specimens and 69 adjacent normal tissues were randomly separated into training or validation cohorts at a 7:3 ratio. We identified 7 FRLs that constitute a prognostic signature according to the differential analysis, correlation analysis, univariate regression, and least absolute shrinkage and selection operator (LASSO) Cox analysis. To identify the independence of risk score as a prognostic factor, univariate and multivariate regression analyses were also performed. Furthermore, CIBERSORT was conducted to analyze the immune infiltration of patients in the high-risk and low-risk groups. Subsequently, the differential expression of immune checkpoint and m6A genes was analyzed in the two risk groups. RESULTS: A 7-FRLs prognostic signature of ccRCC was developed to distinguish patients into high-risk and low-risk groups with significant survival differences. This signature has great prognostic performance, with the area under the curve (AUC) for 1, 3, and 5 years of 0.713, 0.700, 0.726 in the training set and 0.727, 0.667, and 0.736 in the testing set, respectively. Moreover, this signature was significantly associated with immune infiltration. Correlation analysis showed that risk score was positively correlated with regulatory T cells (Tregs), activated CD4 memory T cells, CD8 T cells and follicular helper T cells, whereas it was inversely correlated with monocytes and M2 macrophages. In addition, the expression of fourteen immune checkpoint genes and nine m6A-related genes varied significantly between the two risk groups. CONCLUSION: We established a novel FRLs-based prognostic signature for patients with ccRCC, containing seven lncRNAs with precise predictive performance. The FRLs prognostic signature may play a significant role in antitumor immunity and provide a promising idea for individualized targeted therapy for patients with ccRCC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-022-01418-2.