Related Experiment Video For Differentiated thyroid carcinoma
Updated: Jun 26, 2026

A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease
Published on: January 10, 2025
Integrated microbiome and metabolome analysis reveals a novel interplay between gut microbiota and metabolites in
Xue Jiang1, Qian Liu2, Dongkun Xu2
1Department of Nuclear Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China.
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.
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