Suppr超能文献

一个新型预后相关 N-甲基鸟苷长链非编码 RNA 标志物在透明细胞肾细胞癌中的研究。

A novel prognostic N-methylguanosine-related long non-coding RNA signature in clear cell renal cell carcinoma.

机构信息

School of Stomatology, Zunyi Medical University, Zunyi, 563000, Guizhou, China.

Department of Clinical, Zunyi Medical and Pharmaceutical College, Zunyi, 563000, Guizhou, China.

出版信息

Sci Rep. 2023 Oct 27;13(1):18454. doi: 10.1038/s41598-023-45287-w.

Abstract

Clear cell renal cell carcinoma (ccRCC) is regulated by methylation modifications and long noncoding RNAs (lncRNAs). However, knowledge of N-methylguanosine (mG)-related lncRNAs that predict ccRCC prognosis remains insufficient. A prognostic multi-lncRNA signature was created using LASSO regression to examine the differential expression of m7G-related lncRNAs in ccRCC. Furthermore, we performed Kaplan-Meier analysis and area under the curve (AUC) analysis for diagnosis. In all, a model based on five lncRNAs was developed. Principal component analysis (PCA) indicated that the risk model precisely separated the patients into different groups. The IC value for drug sensitivity divided patients into two risk groups. High-risk group of patients was more susceptible to A.443654, A.770041, ABT.888, AMG.706, and AZ628. Moreover, a lower tumor mutation burden combined with low-risk scores was associated with a better prognosis of ccRCC. Quantitative real-time polymerase chain reaction (qRT-PCR) exhibited that the expression levels of LINC01507, AC093278.2 were very high in all five ccRCC cell lines, AC084876.1 was upregulated in all ccRCC cell lines except 786-O, and the levels of AL118508.1 and DUXAP8 were upregulated in the Caki-1 cell line. This risk model may be promising for the clinical prediction of prognosis and immunotherapeutic responses in patients with ccRCC.

摘要

透明细胞肾细胞癌(ccRCC)受甲基化修饰和长链非编码 RNA(lncRNA)调控。然而,关于预测 ccRCC 预后的 N-甲基鸟苷(mG)相关 lncRNA 的知识仍然不足。本研究使用 LASSO 回归分析 ccRCC 中 m7G 相关 lncRNA 的差异表达,构建预后多 lncRNA 特征。此外,我们进行了 Kaplan-Meier 分析和曲线下面积(AUC)分析以进行诊断。最终,建立了一个基于五个 lncRNA 的模型。主成分分析(PCA)表明,风险模型能够精确地将患者分为不同的组。IC 值对药物敏感性进行划分,将患者分为两个风险组。高风险组的患者对 A.443654、A.770041、ABT.888、AMG.706 和 AZ628 更敏感。此外,低肿瘤突变负担与低风险评分相结合与 ccRCC 的较好预后相关。定量实时聚合酶链反应(qRT-PCR)显示,LINC01507、AC093278.2 在所有五种 ccRCC 细胞系中的表达水平均非常高,AC084876.1 在除 786-O 以外的所有 ccRCC 细胞系中均上调,AL118508.1 和 DUXAP8 的水平在 Caki-1 细胞系中上调。该风险模型可能有望用于预测 ccRCC 患者的临床预后和免疫治疗反应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8257/10611723/6a5644116b17/41598_2023_45287_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验