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综合微生物组和代谢组分析揭示了分化型甲状腺癌中肠道微生物群与代谢物之间的一种新的相互作用。

Integrated microbiome and metabolome analysis reveals a novel interplay between gut microbiota and metabolites in differentiated thyroid carcinoma.

作者信息

Jiang Xue, Liu Qian, Xu Dongkun, Pang Hua, Shi Yuhong

机构信息

Department of Nuclear Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China.

Department of Nuclear Medicine, The Second Affiliated Hospital of Chengdu Medical College, China National Nuclear Corporation 416 Hospital, Chengdu, 610051, China.

出版信息

BMC Microbiol. 2025 May 31;25(1):346. doi: 10.1186/s12866-025-03877-w.


DOI:10.1186/s12866-025-03877-w
PMID:40448029
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12125819/
Abstract

BACKGROUND: Differentiated Thyroid carcinoma (DTC) is the most prevalent endocrine malignancy. The identification of novel biomarkers for thyroid carcinoma is essential for enhancing our understanding of the molecular mechanisms underlying DTC development. Notably, gut microorganisms and their metabolites play a role in the development of DTC, although their influence is modulated by the host's genetic background and environmental factors. Our study aimed to identify and classify gut microbiota and metabolites associated with DTC. METHODS: 90 patients with a confirmed diagnosis of DTC and 33 healthy volunteers donated stool samples for our analysis. To examine the gut microbiota, we utilized 16 S rRNA gene sequencing, a technique that allows for the identification and classification of microorganisms. Additionally, we employed liquid chromatography-mass spectrometry (LC-MS) to investigate the alterations in metabolites present in thyroid carcinoma patients compared to healthy individuals. RESULTS: The Venn diagram visualized the distribution of bacterial species, with 926 species shared by both groups and 12,225 species unique to DTC patients. Notably, the gut microbiota of DTC patients exhibited higher species richness and diversity compared to healthy individuals. LDA Effect Size (LEfSe) analysis identified Faecalibacterium and Prevotella_9 as more abundant in healthy individuals, while Oscillospiraceae, Subdoligranulum, and Actinobacteriota were significantly more prevalent in DTC patients. We successfully characterized 3255 metabolites in both groups, which were primarily associated with biosynthesis of plant secondary metabolites, neomycin, kanamycin, and gentamicin biosynthesis, bile secretion, and steroid hormone biosynthesis. Among these metabolites, 550 were differentially expressed, with 402 metabolites being highly expressed in DTC patients. Six metabolites exhibiting an area under the curve (AUC) value exceeding 0.87 were identified as potential clinical diagnostic markers for DTC. Furthermore, Spearman's rank correlations were utilized to explore the potential functional relationships between the 10 distinctive microbial species and the top 10 differential metabolites. CONCLUSIONS: The gut microbiota and its associated metabolites may play a crucial role in the development of DTC. The identification of altered metabolites and microbiota in DTC patients suggests their potential as diagnostic markers and therapeutic targets. This offers new insights into the molecular pathogenesis of DTC, providing opportunities for early diagnosis and improved treatment strategies. CLINICAL TRIAL NUMBER: Not applicable.

摘要

背景:分化型甲状腺癌(DTC)是最常见的内分泌恶性肿瘤。确定甲状腺癌的新型生物标志物对于增进我们对DTC发生发展的分子机制的理解至关重要。值得注意的是,肠道微生物及其代谢产物在DTC的发生中起作用,尽管它们的影响受宿主遗传背景和环境因素的调节。我们的研究旨在识别和分类与DTC相关的肠道微生物群和代谢产物。 方法:90例确诊为DTC的患者和33名健康志愿者捐赠粪便样本用于我们的分析。为了检测肠道微生物群,我们采用了16S rRNA基因测序技术,该技术可用于微生物的鉴定和分类。此外,我们采用液相色谱 - 质谱联用(LC-MS)技术来研究甲状腺癌患者与健康个体相比代谢产物的变化。 结果:维恩图直观显示了细菌种类的分布,两组共有926种细菌,DTC患者独有12225种细菌。值得注意的是,与健康个体相比,DTC患者的肠道微生物群表现出更高的物种丰富度和多样性。线性判别分析效应大小(LEfSe)分析确定,健康个体中粪杆菌属和普雷沃菌属_9更为丰富,而颤螺菌科、Subdoligranulum和放线菌门在DTC患者中更为普遍。我们成功鉴定了两组中的3255种代谢产物,这些代谢产物主要与植物次生代谢产物的生物合成、新霉素、卡那霉素和庆大霉素的生物合成、胆汁分泌以及类固醇激素的生物合成有关。在这些代谢产物中,有550种差异表达,其中402种代谢产物在DTC患者中高表达。六种曲线下面积(AUC)值超过0.87的代谢产物被确定为DTC的潜在临床诊断标志物。此外,利用Spearman等级相关性来探索10种独特微生物物种与前10种差异代谢产物之间的潜在功能关系。 结论:肠道微生物群及其相关代谢产物可能在DTC的发生中起关键作用。DTC患者中代谢产物和微生物群的变化表明它们作为诊断标志物和治疗靶点的潜力。这为DTC的分子发病机制提供了新的见解,为早期诊断和改进治疗策略提供了机会。 临床试验编号:不适用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11b7/12125819/5f6663505ba3/12866_2025_3877_Fig9_HTML.jpg
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本文引用的文献

[1]
Potential of natural products and gut microbiome in tumor immunotherapy.

Chin Med. 2024-11-20

[2]
Integrated microbiome and metabolome analysis reveals synergistic efficacy of basil polysaccharide and gefitinib in lung cancer through modulation of gut microbiota and fecal metabolites.

Int J Biol Macromol. 2024-11

[3]
Causal relationship between gut microbiota and thyroid nodules: a bidirectional two-sample Mendelian randomization study.

Front Endocrinol (Lausanne). 2024

[4]
Metabolomic machine learning predictor for diagnosis and prognosis of gastric cancer.

Nat Commun. 2024-2-23

[5]
Thyroid cancer cell metabolism: A glance into cell culture system-based metabolomics approaches.

Exp Cell Res. 2024-2-15

[6]
Harnessing actinobacteria potential for cancer prevention and treatment.

Microb Pathog. 2023-10

[7]
Tissue-resident Lachnospiraceae family bacteria protect against colorectal carcinogenesis by promoting tumor immune surveillance.

Cell Host Microbe. 2023-3-8

[8]
Structure, functions, and diversity of the healthy human microbiome.

Prog Mol Biol Transl Sci. 2022

[9]
The relationships between the gut microbiota and its metabolites with thyroid diseases.

Front Endocrinol (Lausanne). 2022

[10]
High abundance of Lachnospiraceae in the human gut microbiome is related to high immunoscores in advanced colorectal cancer.

Cancer Immunol Immunother. 2023-2

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