一种新的延胡索酸代谢相关的预后特征与喉鳞癌的预后和免疫浸润景观相关。

IF 1.7 4区 医学 Q4 ONCOLOGY
Translational cancer research Pub Date : 2025-07-30 Epub Date: 2025-07-25 DOI:10.21037/tcr-2025-29
Zhang Feng, Yuhang Yang, Jinqing Li, Long Zuo, Meijiao Duan, Bingmin Xu, Zhenlian Xie, Dongzhi Zuo, Xiaosong He, Fangxian Liu, Feng He
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引用次数: 0

摘要

背景:喉鳞状细胞癌是一种侵袭性恶性肿瘤,具有高发病率和高死亡率的特点。癌细胞内的代谢途径经常失调;因此,探索富马酸代谢相关基因(FAMRGs)显得很有趣。我们的目的是确定一个标志性的预后遗传谱,为LSCC患者制定量身定制的管理策略。方法:利用来自癌症基因组图谱(TCGA)、基因表达图谱(GEO)和GeneCards数据库的数据,鉴定与LSCC中富马酸(FA)代谢相关的差异表达基因。为了探索潜在的机制,我们使用基因本体(GO)和京都基因与基因组百科全书(KEGG)进行了分析。此外,我们采用Cox回归和最小绝对收缩和选择算子(LASSO)来开发基于FAMRGs的风险签名。这一特征在TCGA和GEO队列中得到了验证。通过相关分析探讨风险评分与临床特征、微环境特征、药物敏感性的关系。最后,使用基因表达谱交互分析(GEPIA)和人类蛋白图谱(HPA)数据库的数据集验证FAMRGs的表达。此外,通过分子对接和单细胞测序进一步证实了我们研究结果的稳健性。结果:利用ABCC2、ADH7、AQP9、CXCL11、GPT、PAEP、PLCG1 7个基因构建了FA代谢相关喉癌模型。功能分析表明FAMRGs与趋化性和细胞因子-细胞因子受体相互作用密切相关。Kaplan-Meier曲线显示,高风险评分亚组在TCGA和GEO队列中均表现出较差的结果。建立了LSCC生存概率预测曲线图;FAMRGs与免疫检查点显著相关。此外,还确定了六种小分子药物,有望作为治疗LSCC的药物。此外,经HPA和GEPIA数据库证实,CXCL11和AQP9在肿瘤组织中高表达,GPT低表达。分子对接证实了7个核心基因与FA之间的相互作用。单细胞测序证实了这一发现,结果显示LSCC中不同细胞群的表达差异显著。结论:基于7个基因建立了与LSCC FA代谢相关的预后模型。该模型能有效预测LSCC的预后。此外,还鉴定了6种具有潜在治疗价值的小分子药物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel fumaric acid metabolism-related prognostic signature associated with prognosis and immune infiltration landscape in laryngeal squamous cell carcinoma.

Background: Laryngeal squamous cell carcinoma (LSCC) is an aggressive malignant tumor, characterized by high incidence and mortality. Metabolic pathways within cancer cells are frequently dysregulated; thus, exploring fumaric acid metabolism-related genes (FAMRGs) appears interesting. We aimed to identify a signature prognostic genetic profile to develop tailored management strategies for patients with LSCC.

Methods: Data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and GeneCards databases were used to identify differentially expressed genes related to fumaric acid (FA) metabolism in LSCC. To explore the underlying mechanisms, we conducted analyses using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Additionally, we employed Cox regression and the least absolute shrinkage and selection operator (LASSO) to develop a risk signature based on FAMRGs. This signature was validated in TCGA and GEO cohorts. The association of the risk score with clinical characteristics, microenvironmental characteristics, and drug sensitivity was explored by correlation analyses. Finally, expression of FAMRGs was validated using datasets from the Gene Expression Profiling Interactive Analysis (GEPIA) and the Human Protein Atlas (HPA) databases. Moreover, the robustness of our findings was further confirmed through molecular docking and single-cell sequencing.

Results: A FA metabolism-associated model for laryngeal cancer was constructed using seven genes (ABCC2, ADH7, AQP9, CXCL11, GPT, PAEP, and PLCG1). Functional analysis suggested that FAMRGs were strongly associated with the chemotaxis and cytokine-cytokine receptor interaction. High-risk score subgroups, as indicated by the Kaplan-Meier curves, demonstrated poorer outcomes in both TCGA and GEO cohorts. A predictive nomogram was developed for LSCC survival probability; FAMRGs were significantly associated with the immune checkpoints. Additionally, six small molecule drugs that appeared promising as therapeutic agents in combating LSCC were identified. Besides, CXCL11 and AQP9 exhibited significantly high expression in tumor tissues, while GPT showed low expression, as confirmed by the HPA and GEPIA databases. Molecular docking confirmed the interaction between the seven core genes and FA. This finding was corroborated by single-cell sequencing, which revealed significant expression differences across various cell clusters in LSCC.

Conclusions: A prognostic model associated with FA metabolism was established for LSCC based on seven genes. This model can effectively predict LSCC prognosis. Additionally, six small molecule drugs with potential therapeutic value for LSCC were identified.

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来源期刊
CiteScore
2.10
自引率
0.00%
发文量
252
期刊介绍: Translational Cancer Research (Transl Cancer Res TCR; Print ISSN: 2218-676X; Online ISSN 2219-6803; http://tcr.amegroups.com/) is an Open Access, peer-reviewed journal, indexed in Science Citation Index Expanded (SCIE). TCR publishes laboratory studies of novel therapeutic interventions as well as clinical trials which evaluate new treatment paradigms for cancer; results of novel research investigations which bridge the laboratory and clinical settings including risk assessment, cellular and molecular characterization, prevention, detection, diagnosis and treatment of human cancers with the overall goal of improving the clinical care of cancer patients. The focus of TCR is original, peer-reviewed, science-based research that successfully advances clinical medicine toward the goal of improving patients'' quality of life. The editors and an international advisory group of scientists and clinician-scientists as well as other experts will hold TCR articles to the high-quality standards. We accept Original Articles as well as Review Articles, Editorials and Brief Articles.
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