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长链非编码RNA在骨肉瘤中调节细胞死亡。

LncRNAs regulates cell death in osteosarcoma.

作者信息

Zou Ping'an, Tao Zhiwei, Yang Zhengxu, Xiong Tao, Deng Zhi, Chen Qincan, Niu Li

机构信息

Bone and Soft Tissue Sarcoma Department, Jiangxi Cancer Hospital, No. 519 Beijing East Road, Nanchang, 330029, China.

CheerLand Clinical Laboratory Co., Ltd., Peking University Medical Industrial Park, Zhongguancun Life Science Park, Beijing, 100000, China.

出版信息

Sci Rep. 2025 Jul 2;15(1):22592. doi: 10.1038/s41598-025-04440-3.

Abstract

Despite improvements, prognosis in osteosarcoma patients remains poor, making it essential to identify additional and more robust therapeutic targets. Non-apoptotic receptor-mediated cell death (RCD), which plays a crucial role in the pathogenesis of OS, is one avenue actively pursued as an alternative therapeutic target in OS. Long non-coding RNAs (lncRNAs) also play a diverse role in OS pathogenesis, and numerous studies have shown that they are attractive therapeutic targets in OS. However, whether lncRNA also plays a role in non-apoptotic RCD in OS is currently unknown. The objective of the current study was to identify if a functional lncRNA-based gene signature exists that regulates non-apoptotic RCD. We systematically screened immune-related lncRNAs associated with ferroptosis, necroptosis, and pyroptosis using the Pearson correlation algorithm (|Pearson R|> 0.4, P < 0.01) on 88 osteosarcoma patients and 122 normal controls that were selected from the TARGET and GETx databases. Univariate Cox regression analysis was employed to identify lncRNAs associated with osteosarcoma treatment. Three machine learning algorithms-Support Vector Machine, Random Forest, and Generalized Linear Model-were utilized to select feature genes. In low- and high-risk groups, immune infiltration was analyzed using CIBERSORT and gene set enrichment analysis. To verify the mechanism of signature lncRNAs, proteins related to pyroptosis, ferroptosis, and necroptosis were assessed via a combination of in vitro assays. LASSO regression analysis led to constructing a prognostic risk model consisting of four lncRNAs: AC006033.2, AC124798.1, LINC01517, and L3MBTL4-AS1. The AUC values for 1-, 3-, and 5-year survival in the testing set were 0.739, 0.809, and 0.708, respectively, while in the entire cohort, the AUC values were 0.849, 0.881, and 0.776, respectively, indicating high reliability and accuracy of the risk model. The high-risk group exhibited a worse prognosis. Five clusters were identified through non-negative matrix factorization clustering, revealing differences in immune infiltration and the tumor microenvironment. Quantitative polymerase chain reaction analysis showed that four lncRNAs were highly expressed in osteosarcoma, with LINC01517 being particularly associated with poor prognosis. Notably, silencing LINC01517 inhibited in vitro cell proliferation, activated NLRP3/caspase-1/GSDMD-mediated pyroptosis, promoted ferroptosis, and enhanced necroptosis in osteosarcoma cells. The non-apoptotic RCD-related lncRNA signature identified in this study provides valuable insights that will aid future exploration of these prognostic biomarkers as potential therapeutic targets for osteosarcoma treatment.

摘要

尽管有所改善,但骨肉瘤患者的预后仍然很差,因此确定更多更强有力的治疗靶点至关重要。非凋亡性受体介导的细胞死亡(RCD)在骨肉瘤发病机制中起关键作用,是骨肉瘤中作为替代治疗靶点而积极探索的途径之一。长链非编码RNA(lncRNA)在骨肉瘤发病机制中也发挥着多种作用,大量研究表明它们是骨肉瘤中有吸引力的治疗靶点。然而,lncRNA是否也在骨肉瘤的非凋亡性RCD中发挥作用目前尚不清楚。本研究的目的是确定是否存在调节非凋亡性RCD的基于lncRNA的功能性基因特征。我们使用Pearson相关算法(|Pearson R|> 0.4,P < 0.01),对从TARGET和GETx数据库中选取的88例骨肉瘤患者和122例正常对照进行系统筛选,以寻找与铁死亡、坏死性凋亡和焦亡相关的免疫相关lncRNA。采用单因素Cox回归分析来鉴定与骨肉瘤治疗相关的lncRNA。利用三种机器学习算法——支持向量机、随机森林和广义线性模型——来选择特征基因。在低风险和高风险组中,使用CIBERSORT和基因集富集分析来分析免疫浸润情况。为了验证特征lncRNA的机制,通过体外实验组合评估了与焦亡、铁死亡和坏死性凋亡相关的蛋白质。LASSO回归分析构建了一个由四个lncRNA组成的预后风险模型:AC006033.2、AC124798.1、LINC01517和L3MBTL4-AS1。测试集中1年、3年和5年生存率的AUC值分别为0.739、0.809和0.708,而在整个队列中,AUC值分别为0.849、0.881和0.776,表明风险模型具有高可靠性和准确性。高风险组预后较差。通过非负矩阵分解聚类鉴定出五个簇,揭示了免疫浸润和肿瘤微环境的差异。定量聚合酶链反应分析表明,四个lncRNA在骨肉瘤中高表达,其中LINC01517与预后不良特别相关。值得注意的是,沉默LINC01517可抑制体外细胞增殖,激活NLRP3/半胱天冬酶-1/GSDMD介导的焦亡,促进铁死亡,并增强骨肉瘤细胞中的坏死性凋亡。本研究中鉴定出的与非凋亡性RCD相关的lncRNA特征提供了有价值的见解,将有助于未来探索这些预后生物标志物作为骨肉瘤治疗的潜在治疗靶点。

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