样本编号	SAMC5203747
外部数据库编号	GSA-Human: HRS1924691
样品名称	F217
样本标题	16sRNA sequencing of colorectal cancer patient: stoolF217
样品类型	Environmental/Metagenome Genomic Sequences MIMS.me -- human-gut
物种名称	human gut metagenome
描述信息	Stool sample from CRC patient with lymph node metastasis before treatment
样本属性	*该样本包含更多受控访问信息，请通过GSA-Human系统申请项目HRA011714数据获取。
发布日期	2025-06-04
项目编号	PRJCA040945
提交者	Weizhong Tang (tangweizhong@gxmu.edu.cn)
提交单位	Guangxi Medical University Cancer Hospital
提交日期	2025-06-04

样本包含数据信息

资源名称	描述
GSA-Human (1)	-
HRA011714 (Controlled Access)	This study focuses on the significant role between gut microbiota and lymph node metastasis (LNM) in colorectal cancer (CRC). By conducting 16S rRNA sequencing on fecal samples from 147 CRC patients and combining it with the linear discriminant analysis effect size algorithm, we successfully identified significant differences in the gut microbiota between patients with LNM and those with no lymph node metastasis (NLNM). This study reveals that Bacteroides plebeius may play an important role in the progression of CRC, with its mechanism potentially involving changes in immune modulation and metabolic pathways. The classification model constructed based on gut microbiota characteristics can predict LNM status of CRC, providing a new perspective for personalized and precision treatment of CRC patients.

资源名称

描述

GSA-Human (1)

HRA011714 (Controlled Access)

This study focuses on the significant role between gut microbiota and lymph node metastasis (LNM) in colorectal cancer (CRC). By conducting 16S rRNA sequencing on fecal samples from 147 CRC patients and combining it with the linear discriminant analysis effect size algorithm, we successfully identified significant differences in the gut microbiota between patients with LNM and those with no lymph node metastasis (NLNM). This study reveals that Bacteroides plebeius may play an important role in the progression of CRC, with its mechanism potentially involving changes in immune modulation and metabolic pathways. The classification model constructed based on gut microbiota characteristics can predict LNM status of CRC, providing a new perspective for personalized and precision treatment of CRC patients.