Clinical significance and immune landscape of cuproptosis-related lncRNAs in kidney renal clear cell carcinoma: a bioinformatical analysis

被引:5
作者
Li, Ding [1 ,2 ,3 ,4 ]
Wu, Xuan [5 ]
Song, Wenping [1 ,2 ,3 ,4 ]
Cheng, Cheng [5 ]
Hao, Lidan [5 ]
Zhang, Wenzhou [1 ,2 ,3 ,4 ]
机构
[1] Affiliated Canc Hosp Zhengzhou Univ, Dept Pharm, Zhengzhou 450008, Peoples R China
[2] Henan Canc Hosp, Zhengzhou 450008, Peoples R China
[3] Henan Canc Hosp, Henan Engn Res Ctr Tumor Precis Med & Comprehens, Zhengzhou, Peoples R China
[4] Henan Canc Hosp, Henan Prov Key Lab Anticanc Drug Res, Zhengzhou, Peoples R China
[5] Affiliated Canc Hosp Zhengzhou Univ, Dept Internal Med, Zhengzhou, Peoples R China
关键词
Cuproptosis; lncRNA; prognosis; drug sensitivity; kidney renal clear cell carcinoma; GUIDELINES; THERAPIES; TRENDS;
D O I
10.21037/atm-22-5204
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: Kidney renal clear cell carcinoma (KIRC) is considered an immunogenic tumor. Cuproptosis is a newly identified copper-induced regulated cell death that relies on mitochondria respiration. Long noncoding RNAs (lncRNAs) have emerged as significant players in tumorigenesis and metastasis. However, there is a huge knowledge gap on the prognostic role of cuproptosis-related lncRNAs in KIRC. And, the clinical value of them is still unknown. Here, we aimed to develop a cuproptosis-related lncRNA prognostic signature in KIRC. Methods: The messenger RNA (mRNA)/lncRNA expression profiles and the clinical information including age, gender, tumor stage, grade, and overall survival (OS) were acquired from The Cancer Genome Atlas (TCGA) database. The included KIRC samples were further randomly assigned into training (n=258) or testing (n=257) data sets. We performed Pearson correlation analysis to identify the cuproptosis-related lncRNAs and then constructed the prognostic signature using Cox regression analysis and LASSO algorithm. Subsequently, Kaplan-Meier survival analysis, a nomogram, and receiver operating characteristic (ROC) curve were performed to assess the predictive performance of the signature. Moreover, the immune characteristics and drug sensitivity related to the signature were also explored. Results: The signature comprised 7 cuproptosis-related lncRNAs. The patients with a low-risk score had superior OS compared with those with a high-risk score. The survival rates of the high- and low-risk groups were 44.96% and 83.72% (P<0.001). The area under the curve (AUC) value for 1-, 3-, 5-year survival rate reached 0.814, 0.762 and 0.825, respectively. In addition, a nomogram was also generated; the AUC was 0.785 for risk score, higher than that for age (0.593), gender (0.489), grade (0.679), and stage (0.721). The high-risk group had more enriched immune- and tumor-related genes. Patients with low-risk scores were more sensitive to immunotherapy and the small molecular drugs GSK1904529A, tipifarnib, BX-912, FR-180204, and GSK1070916. Meanwhile, the high-risk group tended to be more sensitive to pyrimethamine, MS-275, and CGP-60474. Conclusions: Collectively, we constructed a cuproptosis-related lncRNA prognostic signature with a higher predictive accuracy compared to multiple clinicopathological parameters, which may provide vital guidance for therapeutic strategies in KIRC. Combination of more prognostic biomarkers may further improve the accuracy.
引用
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页数:17
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