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基于机器学习的甲状腺癌患者肠道微生态特征分析

李涛 罗志宇 丁亚杰

杭州师范大学学报(自然科学版)2026,Vol.25Issue(4):392-400,9.
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杭州师范大学学报(自然科学版)2026,Vol.25Issue(4):392-400,9.DOI:10.19926/j.cnki.issn.1674-232X.2026.02.111

基于机器学习的甲状腺癌患者肠道微生态特征分析

Analysis of gut microecological characteristics in thyroid cancer patients based on machine learning

李涛 1罗志宇 2丁亚杰3

作者信息

  • 1. 杭州师范大学附属医院,浙江杭州
  • 2. 江苏三黍生物科技有限公司,江苏南通
  • 3. 上海中医药大学附属龙华医院,上海市中医肿瘤临床医学研究中心,上海
  • 折叠

摘要

Abstract

To identify diagnostic microbial biomarkers,machine learning algorithms were used to analyze the gut microbiome profiles of patients with thyroid cancer.Gut microbiome sequencing data of thyroid cancer were obtained from the National Center for Biotechnology Information(NCBI)database.The Kraken2 tool was used for taxonomic annotation and construction of an operational taxonomic unit(OTU)abundance table.The H2O automated machine learning platform was applied,integrating algorithms such as generalized linear model(GLM),distributed random forest(DRF),and deep learning to screen for key characteristic microorganisms,combined with the Wilcoxon rank-sum test to analyze abundance differences between groups.Through cross-validation across multiple models,key OTUs including Sutterella,Emergencia,Lactococcus,and Carnobacterium were identified.Differential analysis showed that,compared with the healthy control group,the abundance of Sutterella in the gut of thyroid cancer patients was significantly decreased(P<0.001),while the abundances of Emergencia,Lactococcus,and Carnobacterium were significantly increased(P<0.001).These results indicate that specific alterations exist in the gut microbiota structure of thyroid cancer patients.The identified microorganisms may serve as auxiliary diagnostic biomarkers and novel targets for research on thyroid-gut axis.

关键词

甲状腺癌/肠道菌群/生物信息学/机器学习

Key words

thyroid cancer/gut microbiota/bioinformatics/machine learning

分类

医药卫生

引用本文复制引用

李涛,罗志宇,丁亚杰..基于机器学习的甲状腺癌患者肠道微生态特征分析[J].杭州师范大学学报(自然科学版),2026,25(4):392-400,9.

基金项目

国家中医药管理局高水平中医药重点学科建设项目(zyyzdxk-2023063) (zyyzdxk-2023063)

杭州师范大学学报(自然科学版)

1674-232X

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