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铁死亡相关长链非编码RNA:区分肿瘤微环境的异质性并预测膀胱癌的免疫治疗反应

Ferroptosis-related lncRNAs: Distinguishing heterogeneity of the tumour microenvironment and predicting immunotherapy response in bladder cancer.

作者信息

Yang Zhan, Li Xiaoqi, Zhou Lijun, Luo Yaxian, Zhan Ning, Ye Yifan, Liu Zhichao, Zhang Xiaoting, Qiu Tao, Lin Lining, Peng Lianjie, Hu Yiming, Pan Chaoran, Sun Mouyuan, Zhang Yan

机构信息

Department of Urology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China.

Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, 310000, China.

出版信息

Heliyon. 2024 May 31;10(11):e32018. doi: 10.1016/j.heliyon.2024.e32018. eCollection 2024 Jun 15.

DOI:10.1016/j.heliyon.2024.e32018
PMID:38867969
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11168393/
Abstract

Ferroptosis, a cell death pathway dependent on iron, has been shown in research to play a role in the development, advancement, and outlook of tumours through ferroptosis-related lncRNAs (FRLRs). However, the value of the FRLRs in bladder cancer (BLCA) has not been thoroughly investigated. This research project involved developing a predictive model using ten specific FRLRs (AC099850.4, AL731567.1, AL133415.1, AC021321.1, SPAG5-AS1, HMGA2-AS1, RBMS3-AS3, AC006160.1, AL583785.1, and AL662844.4) through univariate COX and LASSO regression techniques. The validation of this signature as a standalone predictor was confirmed in a group of 65 patients from the urology bladder tumour database at the First Affiliated Hospital of Wenzhou Medical University in Wenzhou, China. Patients were categorized based on their median risk score into either a low-risk group or a high-risk group. Enrichment analysis identified possible molecular mechanisms that could explain the variations in clinical outcomes observed in high-risk and low-risk groups. Moreover, we explored the correlation between FLPS and immunotherapy-related indicators. The ability of FLPS to forecast the effectiveness of immunotherapy was validated by the elevated levels of immune checkpoint genes (PD-L1, CTLA4, and PD-1) in the group at high risk. We also screened the crucial FRLR (HMGA2-AS1) through congruent expression and prognostic conditions and established a ceRNA network, indicating that HMGA2-AS1 may affect epithelial-mesenchymal transition by modulating the Wnt signalling pathway through the ceRNA mechanism. We identified the top five mRNAs (NFIB, NEGR1, JAZF1, JCAD, and ESM1) based on random forest algorithm and analysed the relationship between HMGA2-AS1, the top five mRNAs, and immunotherapy, and their interactions with drug sensitivities. Our results suggest that patients with BLCA have a greater sensitivity to four drugs (dasatinib, pazopanib, erismodegib and olaparib). Our study provides new insights into the TME, key signalling pathways, genome, and potential therapeutic targets of BLCA, with future guidance for immunotherapy and targeted precision drugs.

摘要

铁死亡是一种依赖铁的细胞死亡途径,研究表明它通过铁死亡相关长链非编码RNA(FRLR)在肿瘤的发生、发展和预后中发挥作用。然而,FRLR在膀胱癌(BLCA)中的价值尚未得到充分研究。本研究项目通过单变量COX和LASSO回归技术,利用十种特定的FRLR(AC099850.4、AL731567.1、AL133415.1、AC021321.1、SPAG5-AS1、HMGA2-AS1、RBMS3-AS3、AC006160.1、AL583785.1和AL662844.4)构建了一个预测模型。在中国温州医科大学附属第一医院泌尿外科膀胱肿瘤数据库的65例患者中,验证了该特征作为独立预测指标的有效性。患者根据其风险评分中位数分为低风险组或高风险组。富集分析确定了可能解释高风险组和低风险组临床结局差异的分子机制。此外,我们探讨了FLPS与免疫治疗相关指标之间的相关性。高风险组免疫检查点基因(PD-L1、CTLA4和PD-1)水平升高,验证了FLPS预测免疫治疗疗效的能力。我们还通过共表达和预后情况筛选出关键的FRLR(HMGA2-AS1),并建立了ceRNA网络,表明HMGA2-AS1可能通过ceRNA机制调节Wnt信号通路影响上皮-间质转化。我们基于随机森林算法确定了前五个mRNA(NFIB、NEGR1、JAZF1、JCAD和ESM1),并分析了HMGA2-AS1、前五个mRNA与免疫治疗之间的关系,以及它们与药物敏感性的相互作用。我们的结果表明,BLCA患者对四种药物(达沙替尼、帕唑帕尼、厄立替尼和奥拉帕尼)更敏感。我们的研究为BLCA的肿瘤微环境、关键信号通路、基因组和潜在治疗靶点提供了新的见解,为免疫治疗和靶向精准药物提供了未来指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a8f/11168393/70145a4b27b6/gr7.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a8f/11168393/f1069eb9c337/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a8f/11168393/a31bf73aa064/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a8f/11168393/aa2f01aa1f92/gr2.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a8f/11168393/fc811f9c222d/gr5.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a8f/11168393/70145a4b27b6/gr7.jpg

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