Combined Metabolomic Analysis of Plasma and Tissue Reveals a Prognostic Risk Score System and Metabolic Dysregulation in Esophageal Squamous Cell Carcinoma
Combined Metabolomic Analysis of Plasma and Tissue Reveals a Prognostic Risk Score System and Metabolic Dysregulation in Esophageal Squamous Cell Carcinoma
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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
DOI：
10.3389/fonc.2020.01545
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发表时间：
2020-08-26
影响因子：
4.7
通讯作者：
Mao, Weimin
中科院分区：
文献类型：
--
作者：
Chen, Zhongjian;Dai, Yalan;Mao, Weimin
背景：食管鳞癌(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的发展有关，但还没有发现预测预后的代谢生物标志物或潜在的治疗代谢靶点。方法：采用高效液相-质谱联用代谢组学和Kaplan-Meier分析方法，对276例食管癌根治性切除患者的部分循环代谢产物进行了研究。对23对食管癌组织样本进行组织代谢组学分析，以发现食管癌组织中的代谢异常。采用支持向量机递归特征消除和LIMMA差异表达分析相结合的方法，从179对食管癌组织的转录数据中筛选出有前景的特征基因。与基因和代谢物的联合途径分析确定了ESCC的相关代谢途径和靶点。结果：4种代谢产物犬尿氨酸、1-肉豆蔻酰甘油-3-磷胆碱(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改善了肿瘤-淋巴结-转移分期系统的预后表现，并能够对ESCC的风险进行分层。结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，发现犬尿氨酸途径异常是食管癌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在食管癌组织中的积聚，以及吲哚胺2，3-双加氧酶1的上调。结论：这项工作首次确定了四种潜在的预测循环代谢物。此外，在ESCC中，犬尿氨酸途径代谢被证明是色氨酸-犬尿氨酸代谢上调。结果不仅提供了一个基于代谢物的预后危险评分系统，而且提高了对ESCC发生发展的分子基础的认识，并为ESCC的潜在治疗靶点提供了新的靶点。
Background: 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. Method: 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. Results: 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. Conclusions: 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.