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基于铁死亡相关长链非编码RNA表达构建肝癌预后模型及其预测免疫治疗反应和免疫相关不良反应的潜力。

Construction of a prognostic model for HCC based on ferroptosis-related lncRNAs expression and its potential to predict the response and irAEs of immunotherapy.

作者信息

Dong Liangbo, Zhou Shengnan, Bai Xuesong, He Xiaodong

机构信息

Department of General Surgery, Peking Union Medical College Hospital (CAMS), Beijing, China.

Chinese Academy of Medical Sciences and Peking Union Medical College, Dongcheng, China.

出版信息

Front Pharmacol. 2023 Mar 13;14:1090895. doi: 10.3389/fphar.2023.1090895. eCollection 2023.

DOI:10.3389/fphar.2023.1090895
PMID:36992841
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10040586/
Abstract

Ferroptosis is an iron-dependent programmed cell death process, and studies have confirmed that it plays an important regulatory role in the occurrence and development of various malignancies including hepatocellular carcinoma (HCC). In addition, the role of abnormally expressed long non-coding RNAs (lncRNAs) in regulating and driving the occurrence and development of HCC has attracted more and more attention. However, there is still a lack of research on the role of ferroptosis-related lncRNAs in the prognosis prediction of HCC patients. In this study, we used the Pearson test method to analyze the association between differentially expressed lncRNAs and ferroptosis-related genes in HCC and normal tissues obtained from The Cancer Genome Atlas (TCGA), and found 68 aberrantly expressed and prognosis-related ferroptosis-related lncRNAs. Based on this, we established an HCC prognostic model composed of 12 ferroptosis-related lncRNAs. In addition, HCC patients were divided into a high-risk group and a low-risk group according to the risk score of this 12 ferroptosis-related lncRNAs prognostic model. Gene enrichment analysis indicated that ferroptosis-related lncRNA-based expression signatures may regulate HCC immune microenvironment signaling pathways through ferroptosis, chemical carcinogenesis-reactive oxygen species, and NK cell-mediated cytotoxicity pathways. In addition, immune cell correlation analysis showed that there were significant differences in immune infiltrating cell subtypes, such as Th cells, macrophages, monocytes, and Treg cells between the two groups. In addition, the expression of multiple immune checkpoint molecules was found to be significantly increased in the high-risk group (eg, PD1, CTLA-4, CD86, etc.). Our research provides a new method for predicting prognosis using a ferroptosis-related lncRNA expression signature prognostic model in hepatocellular carcinoma. And it provides new tools for predicting patient response and adverse effects of immunotherapy. In conclusion, ferroptosis-related lncRNA expression signatures can be used to construct a prognostic prediction model to predict the overall survival of HCC patients, and can be used as an independent influencing factor for prognosis. Further analysis showed that ferroptosis-related lncRNAs may affect the efficacy of immunotherapy in patients with HCC by altering the tumor microenvironment, so this model may serve as a new indicator of the response and irAEs of HCC to immunotherapy.

摘要

铁死亡是一种铁依赖性程序性细胞死亡过程,研究证实其在包括肝细胞癌(HCC)在内的各种恶性肿瘤的发生和发展中起重要调节作用。此外,异常表达的长链非编码RNA(lncRNA)在调节和驱动HCC发生发展中的作用越来越受到关注。然而,关于铁死亡相关lncRNA在HCC患者预后预测中的作用仍缺乏研究。在本研究中,我们使用Pearson检验方法分析了从癌症基因组图谱(TCGA)获得的HCC组织和正常组织中差异表达的lncRNA与铁死亡相关基因之间的关联,发现了68个异常表达且与预后相关的铁死亡相关lncRNA。基于此,我们建立了一个由12个铁死亡相关lncRNA组成的HCC预后模型。此外,根据这个12个铁死亡相关lncRNA预后模型的风险评分,将HCC患者分为高风险组和低风险组。基因富集分析表明,基于铁死亡相关lncRNA的表达特征可能通过铁死亡、化学致癌-活性氧和NK细胞介导的细胞毒性途径调节HCC免疫微环境信号通路。此外,免疫细胞相关性分析表明,两组之间的免疫浸润细胞亚型,如Th细胞、巨噬细胞、单核细胞和Treg细胞存在显著差异。此外,发现多个免疫检查点分子在高风险组中的表达显著增加(如PD1、CTLA-4、CD86等)。我们的研究为使用铁死亡相关lncRNA表达特征预后模型预测肝细胞癌预后提供了一种新方法。并且为预测患者对免疫治疗的反应和不良反应提供了新工具。总之,铁死亡相关lncRNA表达特征可用于构建预后预测模型以预测HCC患者的总生存期,并可作为预后的独立影响因素。进一步分析表明,铁死亡相关lncRNA可能通过改变肿瘤微环境影响HCC患者免疫治疗的疗效,因此该模型可能作为HCC对免疫治疗反应和免疫相关不良反应的新指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d90/10040586/bb54658de389/fphar-14-1090895-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d90/10040586/1780c73a684e/fphar-14-1090895-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d90/10040586/f218f43faf4c/fphar-14-1090895-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d90/10040586/99de156332c5/fphar-14-1090895-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d90/10040586/bb54658de389/fphar-14-1090895-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d90/10040586/1780c73a684e/fphar-14-1090895-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d90/10040586/5995c9145d77/fphar-14-1090895-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d90/10040586/f83518a25cb1/fphar-14-1090895-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d90/10040586/f218f43faf4c/fphar-14-1090895-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d90/10040586/99de156332c5/fphar-14-1090895-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d90/10040586/bb54658de389/fphar-14-1090895-g006.jpg

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