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血浆和组织的联合代谢组学分析揭示了食管鳞状细胞癌的预后风险评分系统和代谢失调

Combined Metabolomic Analysis of Plasma and Tissue Reveals a Prognostic Risk Score System and Metabolic Dysregulation in Esophageal Squamous Cell Carcinoma.

作者信息

Chen Zhongjian, Dai Yalan, Huang Xiancong, Chen Keke, Gao Yun, Li Na, Wang Ding, Chen Aiping, Yang Qingxia, Hong Yanjun, Zeng Su, Mao Weimin

机构信息

College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.

Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, China.

出版信息

Front Oncol. 2020 Aug 26;10:1545. doi: 10.3389/fonc.2020.01545. eCollection 2020.

Abstract

Esophageal squamous cell carcinoma (ESCC) is a gastrointestinal malignancy with a poor prognosis. Although studies have shown metabolic reprogramming to be linked to ESCC development, no prognostic metabolic biomarkers or potential therapeutic metabolic targets have been identified. The present study investigated some circulating metabolites associated with overall survival in 276 curatively resected ESCC patients using liquid chromatography/mass spectrometry metabolomics and Kaplan-Meier analysis. Tissue metabolomic analysis of 23-paired ESCC tissue samples was performed to discover metabolic dysregulation in ESCC cancerous tissue. A method consisting of support vector machine recursive feature elimination and LIMMA differential expression analysis was utilized to select promising feature genes within transcriptomic data from 179-paired ESCC tissue samples. Joint pathway analysis with genes and metabolites identified relevant metabolic pathways and targets for ESCC. Four metabolites, kynurenine, 1-myristoyl-glycero-3-phosphocholine (LPC(14:0)sn-1), 2-piperidinone, and hippuric acid, were identified as prognostic factors in the preoperative plasma from ESCC patients. A risk score consisting of kynurenine and LPC(14:0)sn-1 significantly improved the prognostic performance of the tumor-node-metastasis staging system and was able to stratify risk for ESCC. Combined tissue metabolomic analysis and support vector machine recursive feature elimination gene selection revealed dysregulated kynurenine pathway as an important metabolic feature of ESCC, including accumulation of tryptophan, formylkynurenine, and kynurenine, as well as up-regulated indoleamine 2,3-dioxygenase 1 in ESCC cancerous tissue. This work identified for the first time four potential prognostic circulating metabolites. In addition, kynurenine pathway metabolism was shown to be up-regulated tryptophan-kynurenine metabolism in ESCC. Results not only provide a metabolite-based risk score system for prognosis, but also improve the understanding of the molecular basis of ESCC onset and progression, and as well as novel potential therapeutic targets for ESCC.

摘要

食管鳞状细胞癌(ESCC)是一种预后较差的胃肠道恶性肿瘤。尽管研究表明代谢重编程与ESCC的发生发展有关,但尚未确定预后代谢生物标志物或潜在的治疗性代谢靶点。本研究使用液相色谱/质谱代谢组学和Kaplan-Meier分析,调查了276例接受根治性切除的ESCC患者中一些与总生存期相关的循环代谢物。对23对ESCC组织样本进行组织代谢组学分析,以发现ESCC癌组织中的代谢失调。利用支持向量机递归特征消除和LIMMA差异表达分析组成的方法,从179对ESCC组织样本的转录组数据中选择有前景的特征基因。对基因和代谢物进行联合通路分析,确定了ESCC相关的代谢通路和靶点。四种代谢物,即犬尿氨酸、1-肉豆蔻酰甘油-3-磷酸胆碱(LPC(14:0)sn-1)、2-哌啶酮和马尿酸,被确定为ESCC患者术前血浆中的预后因素。由犬尿氨酸和LPC(14:0)sn-1组成的风险评分显著提高了肿瘤-淋巴结-转移分期系统的预后性能,并能够对ESCC的风险进行分层。联合组织代谢组学分析和支持向量机递归特征消除基因选择揭示,犬尿氨酸途径失调是ESCC的一个重要代谢特征,包括色氨酸、甲酰犬尿氨酸和犬尿氨酸的积累,以及ESCC癌组织中吲哚胺2,3-双加氧酶1的上调。这项工作首次确定了四种潜在的预后循环代谢物。此外,ESCC中犬尿氨酸途径代谢显示色氨酸-犬尿氨酸代谢上调。研究结果不仅提供了一种基于代谢物的预后风险评分系统,还增进了对ESCC发生和发展分子基础的理解,以及ESCC新的潜在治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e224/7479226/a3e3c09ab30e/fonc-10-01545-g0001.jpg

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