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多平台代谢组学揭示早期食管鳞状细胞癌的可能生物标志物。

A multi-platform metabolomics reveals possible biomarkers for the early-stage esophageal squamous cell carcinoma.

机构信息

Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, PR China.

The Affiliated Tumor Hospital of Harbin Medical University, Harbin Medical University, Harbin, PR China.

出版信息

Anal Chim Acta. 2022 Aug 8;1220:340038. doi: 10.1016/j.aca.2022.340038. Epub 2022 Jun 8.

Abstract

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is one of the most prevalent types of upper gastrointestinal malignancies. This work aimed to identify potential biomarkers for early screening for ESCC and characterize the systemic metabolic disturbances underlying ESCC using multi-platform metabolomics analysis.

METHODS

We divided 239 patients (the early-stage ESCC patients, n = 132; Healthy controls, n = 107) into discovery and validation sets after matching age and sex. Integrated statistical and multi-platform serum metabolomics analyses were used to screen and validate significant metabolites linked to ESCC patients.

RESULTS

Multi-platform metabolomics analyses showed that amino acid and lipid metabolism were crucial in the etiology of ESCC. Five metabolites, tryptophan (Trp), citrulline, l-carnitine, lysine, and acetyl-carnitine, were selected as potential biomarkers to establish a diagnosis panel, which showed high accuracy in distinguishing ESCC patients from healthy controls (area under the receiver operating characteristic curve, 0.873, 95% confidence interval [CI]: 0.825-0.925).

CONCLUSIONS

This work laid the groundwork for understanding the etiology of ESCC. The diagnostic panel showed potential usefulness in early-stage ESCC diagnosis in clinical practice.

摘要

背景

食管鳞状细胞癌(ESCC)是最常见的上消化道恶性肿瘤之一。本研究旨在通过多组学代谢组学分析,鉴定 ESCC 早期筛查的潜在生物标志物,并阐明 ESCC 潜在的系统性代谢紊乱。

方法

我们将 239 名患者(早期 ESCC 患者,n=132;健康对照,n=107)按照年龄和性别进行匹配,分为发现和验证组。我们采用整合的统计和多组学血清代谢组学分析方法,筛选和验证与 ESCC 患者相关的显著代谢物。

结果

多组学代谢组学分析表明,氨基酸和脂质代谢在 ESCC 的发病机制中起关键作用。选择 5 种代谢物(色氨酸(Trp)、瓜氨酸、左旋肉碱、赖氨酸和乙酰肉碱)作为潜在的生物标志物来建立诊断模型,该模型在区分 ESCC 患者和健康对照方面具有较高的准确性(受试者工作特征曲线下面积,0.873,95%置信区间[CI]:0.825-0.925)。

结论

本研究为了解 ESCC 的发病机制奠定了基础。该诊断模型在临床实践中对早期 ESCC 诊断具有潜在的应用价值。

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