血清代谢特征与结直肠腺瘤恶化的关系。

IF 3.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Ze Dai, Tong Li, Kecong Lai, Xiaomei Wang, Peng Zhou, Kefeng Hu, Yuping Zhou
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引用次数: 0

摘要

结直肠癌(Colorectal cancer, CRC)可由结直肠腺瘤发展而来,根据其临床特征可进一步分为非晚期腺瘤(non-advanced adenomas, NAAs)和晚期腺瘤(advanced adenomas, AAs)。它们的预后差异很大,NAAs患者的复发率和CRC相关死亡率明显低于AA或CRC患者。尽管血清代谢组学在CRC的早期诊断中显示出希望,但NAA和AA在血清代谢物组成上的差异仍需要进一步阐明。本研究旨在基于CRC不同阶段独特的血清代谢指纹图谱,探索CRC发生发展的机制,探索一种基于血清代谢组学的无创诊断新方法。临床CRC进展队列包含健康对照(NC;n = 40)、NAA (n = 40)、AA (n = 40)、CRC (n = 22)组,采用液相色谱/质谱法进行非靶向代谢组学分析,分析各组血清代谢物特征。对组间代谢物差异进行半定量分析,重点分析NAA组和AA组间存在差异的特定代谢物。最后,根据最小绝对收缩和选择算子(LASSO)回归分析选择可变代谢物,绘制受试者工作特征曲线,评估基于血清代谢物的诊断模型区分NC/NAA群体和AA/CRC群体的有效性。代谢组学分析显示,与CRC组相比,NC组和NAA组的代谢物组成存在显著差异,而AA组的血清代谢物与CRC组相似。与NAA患者相比,AA/CRC患者血清中33种代谢物水平有显著差异,其功能包括甘油磷脂、鞘脂和咖啡因代谢。LASSO回归分析确定了NC/NAA组和AA/CRC组之间的57个差异代谢物变量。使用随机森林算法构建的诊断模型识别效果最好,训练集和测试集的曲线下面积分别为1.000(95%置信区间[CI] 1.000 ~ 1.000)和0.685(95%置信区间[CI] 0.54 ~ 0.830)。血清代谢物的组成对结直肠癌发展的不同阶段具有特异性。AAs患者的血清代谢物组成与结直肠癌患者相似。基于血清代谢物的辅助诊断措施有可能指导腺瘤患者的随访和治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Serum metabolic characteristics associated with the deterioration of colorectal adenomas.

Serum metabolic characteristics associated with the deterioration of colorectal adenomas.

Serum metabolic characteristics associated with the deterioration of colorectal adenomas.

Serum metabolic characteristics associated with the deterioration of colorectal adenomas.

Colorectal cancer (CRC) can evolve from colorectal adenomas, which can be further classified into non-advanced adenomas (NAAs) and advanced adenomas (AAs) based on their clinical characteristics. Their prognoses are vastly different, with patients with NAAs having significantly lower recurrence and CRC-related mortality rates than those with AA or CRC. Although serum metabolomics has shown promise for the early diagnosis of CRC, the differences in serum metabolite composition between NAA and AA still need to be further elucidated. This study aimed to explore the mechanism of CRC occurrence and development based on the unique serum metabolic fingerprints of different stages of CRC and to discover a new non-invasive diagnostic method based on serum metabolomics. A clinical CRC progression cohort containing healthy control (NC; n = 40), NAA (n = 40), AA (n = 40), and CRC (n = 22) groups was constructed, and untargeted metabolomic analysis based on liquid chromatography/mass spectrometry was performed to analyze the serum metabolite characteristics of each group. A semi-quantitative analysis of intergroup metabolite differences was conducted, focusing on specific metabolites that differed in the NAA and AA groups. Finally, variable metabolites were selected based on least absolute shrinkage and selection operator (LASSO) regression analysis, and receiver operating characteristic curves were plotted to evaluate the efficacy of the serum metabolite-based diagnostic model in distinguishing NC/NAA populations from AA/CRC populations. Metabolomic analysis revealed significant differences in the composition of metabolites in the NC and NAA groups compared to the CRC group, whereas the serum metabolites of the AA group were similar to those of the CRC group. The levels of 33 metabolites were significantly different in the serum of AA/CRC patients compared to that of NAA patients, and their functions included glycerophospholipid, sphingolipid, and caffeine metabolism. LASSO regression analysis identified 57 differential metabolite variables between the NC/NAA and AA/CRC groups. The diagnostic model constructed using the random forest algorithm had the best discrimination effect, with areas under the curve of 1.000 (95% confidence interval [CI] 1.000-1.000) and 0.685 (95% CI 0.540-0.830) for the training and testing sets, respectively. The composition of serum metabolites is specific to the different stages of CRC development. The serum metabolite composition of patients with AAs was similar to that of patients with CRC. Auxiliary diagnostic measures based on serum metabolites have the potential to guide the follow-up and treatment of patients with adenoma.

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来源期刊
Scientific Reports
Scientific Reports Natural Science Disciplines-
CiteScore
7.50
自引率
4.30%
发文量
19567
审稿时长
3.9 months
期刊介绍: We publish original research from all areas of the natural sciences, psychology, medicine and engineering. You can learn more about what we publish by browsing our specific scientific subject areas below or explore Scientific Reports by browsing all articles and collections. Scientific Reports has a 2-year impact factor: 4.380 (2021), and is the 6th most-cited journal in the world, with more than 540,000 citations in 2020 (Clarivate Analytics, 2021). •Engineering Engineering covers all aspects of engineering, technology, and applied science. It plays a crucial role in the development of technologies to address some of the world''s biggest challenges, helping to save lives and improve the way we live. •Physical sciences Physical sciences are those academic disciplines that aim to uncover the underlying laws of nature — often written in the language of mathematics. It is a collective term for areas of study including astronomy, chemistry, materials science and physics. •Earth and environmental sciences Earth and environmental sciences cover all aspects of Earth and planetary science and broadly encompass solid Earth processes, surface and atmospheric dynamics, Earth system history, climate and climate change, marine and freshwater systems, and ecology. It also considers the interactions between humans and these systems. •Biological sciences Biological sciences encompass all the divisions of natural sciences examining various aspects of vital processes. The concept includes anatomy, physiology, cell biology, biochemistry and biophysics, and covers all organisms from microorganisms, animals to plants. •Health sciences The health sciences study health, disease and healthcare. This field of study aims to develop knowledge, interventions and technology for use in healthcare to improve the treatment of patients.
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