Suppr超能文献

直肠神经内分泌肿瘤患者肠道微生物群的特征与功能

Characteristics and function of the gut microbiota in patients with rectal neuroendocrine tumors.

作者信息

Gao Yue, Zheng Hongxia, Ye Mujie, Zhou Guozhi, Chen Jinhao, Qiang Xinyun, Bai Jianan, Lu Xintong, Tang Qiyun

机构信息

Department of Geriatric Gastroenterology, Neuroendocrine Tumor Center, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing 210029, Jiangsu Province, China.

出版信息

J Cancer. 2025 Jan 1;16(4):1040-1050. doi: 10.7150/jca.103297. eCollection 2025.

Abstract

The gut microbiota plays a significant role in the initiation and progression of tumors, but its role in rectal neuroendocrine tumors (rNETs) remains unclear. Fecal samples were collected from 19 healthy individuals and 21 rNET patients,with the rNET cohort further divided into metastatic (rNETs-M) and non-metastatic (rNETs-nM) groups. Using metagenomic high-throughput sequencing, we analyzed the diversity, species composition, and functional characteristics of the gut microbiota. We applied a random forest model to identify potential microbial biomarkers for predicting rNET and specifically distinguishing rNETs-M cases. Alpha diversity analysis revealed that species diversity was lower in the rNETs group than in the control group. In contrast, the rNETs-M group exhibited higher species diversity than the rNETs-nM group. Beta diversity analysis demonstrated significant differences in community structure between the rNETs and control groups between the rNET-M and rNETs-nM groups. Notably, in the rNETs group, the abundance of potential pathogens such as Escherichia coli and Shigella was elevated.Furthermore, the rNETs-M group exhibited an increased abundance of potential pathogens such as Alistipes. KEGG enrichment analysis indicated that these distinct microbiota play a significant role in environmental information processing, genetic information processing, and metabolic pathways. Random forest analysis and ROC curve results identified Lachnospira pectinoschiza (AUC=0.885), Parasutterella muris (AUC=0.862), Sodaliphilus pleomorphus(AUC=0.956), Methylobacterium iners (AUC=0.971) as biomarkers with significant discriminatory value.

摘要

肠道微生物群在肿瘤的发生和发展中起着重要作用,但其在直肠神经内分泌肿瘤(rNETs)中的作用仍不清楚。从19名健康个体和21名rNET患者中收集粪便样本,rNET队列进一步分为转移组(rNETs-M)和非转移组(rNETs-nM)。使用宏基因组高通量测序,我们分析了肠道微生物群的多样性、物种组成和功能特征。我们应用随机森林模型来识别预测rNET和特异性区分rNETs-M病例的潜在微生物生物标志物。α多样性分析显示,rNETs组的物种多样性低于对照组。相比之下,rNETs-M组的物种多样性高于rNETs-nM组。β多样性分析表明,rNETs与对照组之间以及rNET-M与rNETs-nM组之间的群落结构存在显著差异。值得注意的是,在rNETs组中,大肠杆菌和志贺氏菌等潜在病原体的丰度升高。此外,rNETs-M组中Alistipes等潜在病原体的丰度增加。KEGG富集分析表明,这些不同的微生物群在环境信息处理、遗传信息处理和代谢途径中发挥着重要作用。随机森林分析和ROC曲线结果确定果胶罗氏菌(AUC=0.885)、鼠副萨特氏菌(AUC=0.862)、多形嗜钠菌(AUC=0.956)、惰性甲基杆菌(AUC=0.971)为具有显著鉴别价值的生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dbab/11786048/7e2e067d89eb/jcav16p1040g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验