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Updated: May 5, 2026

Detection of a Circulating MicroRNA Custom Panel in Patients with Metastatic Colorectal Cancer

Detection of a Circulating MicroRNA Custom Panel in Patients with Metastatic Colorectal Cancer

Published on: March 14, 2019

Machine Learning-Assisted Plasma Metabolomics Identifies a Five-Metabolite Panel for Colorectal Cancer Detection.

Jun-Kai Wong¹, Chung-Hsien Lin¹, Hsin-Yi Wu²

¹Department of Medical Laboratory Science and Biotechnology, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan.

|May 4, 2026

Summary

This summary is machine-generated.

A new five-metabolite panel in plasma shows promise for early colorectal cancer (CRC) detection. This blood test accurately identifies CRC, potentially improving early diagnosis and risk stratification alongside current screening methods.

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Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing

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Published on: September 25, 2011

Area of Science:

Biochemistry
Oncology
Analytical Chemistry

Background:

Colorectal cancer (CRC) is a major global health concern with high mortality rates.
Current screening methods for CRC require improvement, necessitating novel noninvasive diagnostic strategies.

Purpose of the Study:

To develop and validate a noninvasive plasma-based metabolomic signature for early colorectal cancer detection.
To identify specific plasma metabolites that can differentiate CRC patients from healthy individuals.

Main Methods:

An integrated plasma metabolomics workflow using untargeted and targeted liquid chromatography-mass spectrometry.
Machine learning (random forest) for feature prioritization and metabolite annotation.
Validation in independent patient and control cohorts, with diagnostic performance assessed by logistic regression.

Main Results:

Five consistently reduced plasma metabolites (N-methylcytisine, 2-piperidone, theophylline, dl-norleucine, linolenic acid) were identified.
The five-metabolite panel achieved high diagnostic performance (AUC 0.968, 97.9% sensitivity, 89.4% specificity) in the validation cohort.
In vitro assays indicated that the identified metabolites modulate CRC cell migration and invasion.

Conclusions:

The identified five-metabolite plasma signature reflects CRC-associated metabolic alterations.
This panel demonstrates strong discriminatory performance and may serve as a valuable adjunct to existing CRC screening modalities.
The findings support the potential of this metabolomic signature for CRC risk stratification and early detection.