基于代谢组学和16S rDNA测序，探讨ⅰ、ⅱ、ⅲ型甲状腺癌患者代谢物和粪便微生物群的变化

IF 0.9 Q4 GENETICS & HEREDITY

Gene Reports Pub Date : 2025-07-21 DOI:10.1016/j.genrep.2025.102304

Xiang Ao

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引用次数: 0

摘要

了解甲状腺癌不同阶段粪便微生物群和代谢物的变化可能为了解疾病进展和潜在的临床应用生物标志物提供有价值的见解。目的利用代谢组学和16S rDNA测序技术，研究ⅰ、ⅱ、ⅲ期甲状腺癌患者粪便微生物群和代谢物的变化。方法采用代谢组学和16S rDNA测序技术，对I、II、III期甲状腺癌患者粪便微生物群和代谢物的变化进行了全面研究。结果微生物群落结构发生了显著变化。具体来说，与II期和III期患者相比，I期患者的agthobacter丰度明显更高。此外，我们的综合代谢组学分析发现，在I期和II期甲状腺癌患者中，有219种代谢物差异表达（DEMs），其中4种代谢物上调，215种代谢物下调。通过ROC曲线分析，我们确定了两个潜在的生物标志物：5-氨基咪唑（AUC: 0.815）和(R)-5-二磷戊酸（AUC: 0.759），它们具有区分I期和II期甲状腺癌患者的潜力。在I期和III期患者的比较中，大多数dem在III期显著下调，其中12种代谢物上调，217种下调。I期和III期患者之间的潜在生物标志物包括加博沙多、奥拉西坦、n -亚硝基-3-羟基吡啶、N6-（l- 1,3-二羧基丙基）-l-赖氨酸和3-乙基-4-甲基苯酚，AUC值显著大于0.85。在II期和III期患者的比较中，共鉴定出86个dem，其中大多数在III期下调。区分II期和III期患者的关键生物标志物为谷胱甘肽氨基丙基cadaverine、le- ala - arg、Tridecanal和Pregnenolone，通过ROC分析确定，AUC值大于0.85。结论这些发现强调了肠道微生物群、代谢物与甲状腺癌进展之间复杂的相互作用，为甲状腺癌个性化治疗的新时代铺平了道路，为更有效和有针对性的治疗方法提供了希望。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Exploring changes in metabolites and fecal microbiota of I, II, and III thyroid cancer patients based on metabolomics and 16S rDNA sequencing

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Exploring changes in metabolites and fecal microbiota of I, II, and III thyroid cancer patients based on metabolomics and 16S rDNA sequencing

Background

Understanding the alterations in fecal microbiota and metabolites across different stages of thyroid cancer may provide valuable insights into the disease progression and potential biomarkers for clinical application.

Objective

This study aims to investigate the alterations in fecal microbiota and metabolites in stage I, II, and III thyroid cancer patients using metabolomics and 16S rDNA sequencing techniques.

Methods

We conducted a comprehensive study to investigate the alterations in fecal microbiota and metabolites in stage I, II, and III thyroid cancer patients using metabolomics and 16S rDNA sequencing techniques.

Results

Our results revealed notable shifts in the microbial community structure. Specifically, the abundance of agathobacter was significantly higher in stage I patients compared to those in stages II and III. Furthermore, our comprehensive metabolomic analysis identified 219 differentially expressed metabolites (DEMs) between stage I and II thyroid cancer patients, with four metabolites up-regulated and 215 down-regulated in stage II. Through ROC curve analysis, we identified two potential biomarkers: 5-Aminoimidazole (AUC: 0.815) and (R)-5-Diphosphomevalonic acid (AUC: 0.759), which have the potential to distinguish between patients with stage I and stage II thyroid cancer. In the comparison between stages I and III patients, the majority of DEMs were significantly down-regulated in stage III, with 12 metabolites up-regulated and 217 down-regulated. Potential biomarkers between stage I and stage III patients included Gaboxadol, Oxiracetam, N-Nitroso-3-hydroxypyrrolidine, N6-(L-1,3-Dicarboxypropyl)-l-lysine, and 3-Ethyl-4-methylphenol, with AUC values significantly greater than 0.85. In the comparison between stage II and III patients, a total of 86 DEMs were identified, with the majority downregulated in stage III. Key biomarkers distinguishing stage II and stage III patients were Glutathionylaminopropylcadaverine, lle-Ala-Arg, Tridecanal, and Pregnenolone, identified through ROC analysis with AUC values greater than 0.85.

Conclusion

These findings underscore the complex interplay between the gut microbiota, metabolites, and thyroid cancer progression and pave the way for a new era of personalized medicine in thyroid cancer management, offering hope for more effective and targeted treatment approaches.

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来源期刊

Gene Reports Biochemistry, Genetics and Molecular Biology-Genetics

CiteScore

3.30

自引率

7.70%

发文量

246

审稿时长

49 days

期刊介绍： Gene Reports publishes papers that focus on the regulation, expression, function and evolution of genes in all biological contexts, including all prokaryotic and eukaryotic organisms, as well as viruses. Gene Reports strives to be a very diverse journal and topics in all fields will be considered for publication. Although not limited to the following, some general topics include: DNA Organization, Replication & Evolution -Focus on genomic DNA (chromosomal organization, comparative genomics, DNA replication, DNA repair, mobile DNA, mitochondrial DNA, chloroplast DNA). Expression & Function - Focus on functional RNAs (microRNAs, tRNAs, rRNAs, mRNA splicing, alternative polyadenylation) Regulation - Focus on processes that mediate gene-read out (epigenetics, chromatin, histone code, transcription, translation, protein degradation). Cell Signaling - Focus on mechanisms that control information flow into the nucleus to control gene expression (kinase and phosphatase pathways controlled by extra-cellular ligands, Wnt, Notch, TGFbeta/BMPs, FGFs, IGFs etc.) Profiling of gene expression and genetic variation - Focus on high throughput approaches (e.g., DeepSeq, ChIP-Seq, Affymetrix microarrays, proteomics) that define gene regulatory circuitry, molecular pathways and protein/protein networks. Genetics - Focus on development in model organisms (e.g., mouse, frog, fruit fly, worm), human genetic variation, population genetics, as well as agricultural and veterinary genetics. Molecular Pathology & Regenerative Medicine - Focus on the deregulation of molecular processes in human diseases and mechanisms supporting regeneration of tissues through pluripotent or multipotent stem cells.