Department of Urology, The Second Affiliated Hospital of Kunming Medical University, Yunnan Institute of Urology, Kunming, 650000 Yunnan Province, China.
Dis Markers. 2022 May 23;2022:5204831. doi: 10.1155/2022/5204831. eCollection 2022.
Necroptosis, a recently identified type of programmed necrotic cell death, is closely related to the tumorigenesis and development of cancer. However, it remains unclear whether necroptosis-associated long noncoding RNAs (lncRNAs) can be used to predict the prognosis of kidney renal clear cell carcinoma (KIRC). This work was designed to probe the possible prognostic worth of necroptosis-associated lncRNAs along with their impact on the tumor microenvironment (TME) in KIRC.
The Cancer Genome Atlas (TCGA) database was used to extract KIRC gene expression and clinicopathological data. Pearson correlation analysis was used to evaluate necroptosis-associated lncRNAs against 159 known necroptosis-associated genes. To define molecular subtypes, researchers used univariate Cox regression analysis and consensus clustering, as well as clinical significance, TME, and tumor immune cells in each molecular subtype. We develop the necroptosis-associated lncRNA prognostic model using univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis. Patients were divided into high- and low-risk groups according to prognostic model. Moreover, comprehensive analyses, including prognostic value, gene set enrichment analysis (GSEA), immune infiltration, and immune checkpoint gene expression, were performed between the two risk groups. Finally, anticancer drug sensitivity analyses were employed for assessing associations for necroptosis-associated lncRNA expression profile and anticancer drug chemosensitivity.
Through univariate analysis, sixty-nine necroptosis-associated lncRNAs were found to have a significant relationship with KIRC prognosis. Two molecular clusters were identified, and significant differences were found with respect to clinicopathological features and prognosis. The segregation of patients into two risk groups was done by the constructed necroptosis-associated lncRNA model. The survival prognosis, clinical features, degree of immune cell infiltration, and expression of immune checkpoint genes of high-risk and low-risk groups were all shown to vary.
Our study identified a model of necroptosis-associated lncRNA signature and revealed its prognostic role in KIRC. It is expected to provide a reference for the screening of KIRC prognostic markers and the evaluation of immune response.
细胞程序性坏死是一种新近发现的细胞死亡方式，与肿瘤的发生发展密切相关。然而，细胞程序性坏死相关长链非编码 RNA（lncRNA）是否可用于预测肾透明细胞癌（KIRC）的预后尚不清楚。本研究旨在探讨 KIRC 中细胞程序性坏死相关 lncRNA 的预后价值及其对肿瘤微环境（TME）的影响。
利用癌症基因组图谱（TCGA）数据库提取 KIRC 基因表达和临床病理数据。采用 Pearson 相关性分析评估细胞程序性坏死相关 lncRNA 与 159 种已知的细胞程序性坏死相关基因之间的相关性。通过单因素 Cox 回归分析和共识聚类以及每个分子亚型的临床意义、TME 和肿瘤免疫细胞，对 KIRC 进行分子亚型的定义。采用单因素 Cox 回归分析和最小绝对收缩和选择算子（LASSO）回归分析构建细胞程序性坏死相关 lncRNA 预后模型。根据预后模型将患者分为高低风险组。此外，对两组患者进行了全面分析，包括预后价值、基因集富集分析（GSEA）、免疫浸润和免疫检查点基因表达。最后，采用抗癌药物敏感性分析评估细胞程序性坏死相关 lncRNA 表达谱与抗癌药物化疗敏感性的关系。
通过单因素分析，发现 69 个细胞程序性坏死相关 lncRNA 与 KIRC 的预后显著相关。鉴定出两个分子簇，在临床病理特征和预后方面存在显著差异。通过构建的细胞程序性坏死相关 lncRNA 模型将患者分为高低风险组。高风险组和低风险组的生存预后、临床特征、免疫细胞浸润程度和免疫检查点基因表达均存在差异。
本研究构建了一个细胞程序性坏死相关 lncRNA 模型，并揭示了其在 KIRC 中的预后作用。有望为 KIRC 预后标志物的筛选和免疫反应的评估提供参考。
