Identification and predictive machine learning models construction of gut microbiota associated with lymph node metastasis in colorectal cancer.

ABSTRACT: 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). Furthermore, using transcriptome data from 23 CRC patients, we constructed an immune cell infiltration matrix to deeply explore the biological functions associated with LNM. Eventually, using the characteristics of the gut microbiota associated with LNM, we developed random forest (RF) and multilayer perceptron (MLP) machine learning models to predict the LNM status of CRC

SUBMITTER: Wu Y 

PROVIDER: S-EPMC12363233 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature