Feng Rui, Li Haolin, Meng Tong, Fei Mingtian, Yang Cheng
Department of Urology, the First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China.
Institute of Urology, Anhui Medical University, Hefei, Anhui, China.
Discov Oncol. 2024 May 26;15(1):187. doi: 10.1007/s12672-024-01023-y.
This study aimed to construct an m6A and cuproptosis-related long non-coding RNAs (lncRNAs) signature to accurately predict the prognosis of kidney clear cell carcinoma (KIRC) patients using the information acquired from The Cancer Genome Atlas (TCGA) database.
First, the co-expression analysis was performed to identify lncRNAs linked with N6-methyladenosine (m6A) and cuproptosis in ccRCC. Then, a model encompassing four candidate lncRNAs was constructed via univariate, least absolute shrinkage together with selection operator (LASSO), and multivariate regression analyses. Furthermore, Kaplan-Meier, principal component, functional enrichment annotation, and nomogram analyses were performed to develop a risk model that could effectively assess medical outcomes for ccRCC cases. Moreover, the cellular function of NFE4 in Caki-1/OS-RC-2 cultures was elucidated through CCK-8/EdU assessments and Transwell experiments. Dataset outcomes indicated that NFE4 can have possible implications in m6A and cuproptosis, and may promote ccRCC progression.
We constructed a panel of m6A and cuproptosis-related lncRNAs to construct a prognostic prediction model. The Kaplan-Meier and ROC curves showed that the feature had acceptable predictive validity in the TCGA training, test, and complete groups. Furthermore, the m6A and cuproptosis-related lncRNA model indicated higher diagnostic efficiency than other clinical features. Moreover, the NFE4 function analysis indicated a gene associated with m6A and cuproptosis-related lncRNAs in ccRCC. It was also revealed that the proliferation and migration of Caki-1 /OS-RC-2 cells were inhibited in the NFE4 knockdown group.
Overall, this study indicated that NFE4 and our constructed risk signature could predict outcomes and have potential clinical value.
本研究旨在利用从癌症基因组图谱（TCGA）数据库获取的信息，构建一个与m6A和铜死亡相关的长链非编码RNA（lncRNA）特征，以准确预测肾透明细胞癌（KIRC）患者的预后。
首先，进行共表达分析以鉴定与ccRCC中N6-甲基腺苷（m6A）和铜死亡相关的lncRNA。然后，通过单变量、最小绝对收缩与选择算子（LASSO）以及多变量回归分析构建包含四个候选lncRNA的模型。此外，进行了Kaplan-Meier、主成分、功能富集注释和列线图分析，以开发一个能够有效评估ccRCC病例医学结局的风险模型。此外，通过CCK-8/EdU评估和Transwell实验阐明了NFE4在Caki-1/OS-RC-2培养物中的细胞功能。数据集结果表明，NFE4可能在m6A和铜死亡中具有潜在影响，并可能促进ccRCC进展。
我们构建了一组与m6A和铜死亡相关的lncRNA来构建预后预测模型。Kaplan-Meier曲线和ROC曲线表明，该特征在TCGA训练组、测试组和完整组中具有可接受的预测效度。此外，与m6A和铜死亡相关的lncRNA模型显示出比其他临床特征更高的诊断效率。此外，NFE4功能分析表明，在ccRCC中存在一个与m6A和铜死亡相关lncRNA相关的基因。还发现，NFE4敲低组中Caki-1 /OS-RC-2细胞的增殖和迁移受到抑制。
总体而言，本研究表明，NFE4和我们构建的风险特征可以预测结局，并具有潜在的临床价值。
