Serum metabolomics-based diagnostic biomarkers for colorectal cancer: insights and multi-omics validation.

ABSTRACT:

Background

Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide, primarily due to delayed diagnosis. There is an urgent need for sensitive, noninvasive biomarkers that can facilitate early detection and improve clinical outcomes.

Methods

In this study, we performed untargeted metabolomic profiling of serum samples from 715 participants (248 CRC patients and 467 noncancer controls, NCC) using liquid chromatography-mass spectrometry (LC-MS). Differential metabolites were identified through statistical filtering and multivariate analysis, followed by pathway enrichment to elucidate biologically relevant dysregulations. Subsequently, machine learning algorithms, including Support Vector Machine (SVM), Random Forest (RF), eXtreme Gradien

SUBMITTER: Wang T 

PROVIDER: S-EPMC12597806 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature