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与干性相关的长链非编码 RNA 标志物用于预测 ccRCC 患者的预后和肿瘤免疫微环境。

Stemness related lncRNAs signature for the prognosis and tumor immune microenvironment of ccRCC patients.

机构信息

Department of Geriatric Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China.

Department of Orthopedics/Sports Medicine Center, Southwest Hospital, Army Medical University, Chongqing, 400038, China.

出版信息

BMC Med Genomics. 2024 May 31;17(1):150. doi: 10.1186/s12920-024-01920-9.

Abstract

Long non-coding RNAs (lncRNAs) and cancer stem cells (CSCs) are crucial for the growth, migration, recurrence, and medication resistance of tumors. However, the impact of lncRNAs related to stemness on the outcome and tumor immune microenvironment (TIME) in clear cell renal cell carcinoma (ccRCC) is still unclear. In this study, we aimed to predict the outcome and TIME of ccRCC by constructing a stem related lncRNAs (SRlncRNAs) signature. We firstly downloaded ccRCC patients' clinical data and RNA sequencing data from UCSC and TCGA databases, and abtained the differentially expressed lncRNAs highly correlated with stem index in ccRCC through gene expression differential analysis and Pearson correlation analysis. Then, we selected suitable SRlncRNAs for constructing a prognostic signature of ccRCC patients by LASSO Cox regression. Further, we used nomogram and Kaplan Meier curves to evaluate the SRlncRNA signature for the prognose in ccRCC. At last, we used ssGSEA and GSVA to evaluate the correlation between the SRlncRNAs signature and TIME in ccRCC. Finally, We obtained a signtaure based on six SRlncRNAs, which are correlated with TIME and can effectively predict the ccRCC patients' prognosis. The SRlncRNAs signature may be a noval prognostic indicator in ccRCC.

摘要

长链非编码 RNA(lncRNA)和癌症干细胞(CSC)对于肿瘤的生长、迁移、复发和耐药性至关重要。然而,lncRNA 与干性相关对透明细胞肾细胞癌(ccRCC)的结局和肿瘤免疫微环境(TIME)的影响尚不清楚。在这项研究中,我们旨在通过构建与干性相关的 lncRNAs(SRlncRNAs)特征来预测 ccRCC 的结局和 TIME。我们首先从 UCSC 和 TCGA 数据库下载 ccRCC 患者的临床数据和 RNA 测序数据,并通过基因表达差异分析和 Pearson 相关性分析获得与 ccRCC 干细胞指数高度相关的差异表达 lncRNA。然后,我们通过 LASSO Cox 回归选择合适的 SRlncRNAs 来构建 ccRCC 患者的预后特征。进一步,我们使用列线图和 Kaplan-Meier 曲线评估 SRlncRNA 特征在 ccRCC 中的预后。最后,我们使用 ssGSEA 和 GSVA 来评估 SRlncRNAs 特征与 ccRCC 中 TIME 的相关性。最终,我们获得了一个基于六个与 TIME 相关且可有效预测 ccRCC 患者预后的 SRlncRNAs 的特征。SRlncRNAs 特征可能是 ccRCC 的一种新型预后指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ffe/11141027/f3c4f5df848c/12920_2024_1920_Fig1_HTML.jpg

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