# Identification of clinically relevant profiles in colorectal cancer through integrated analysis of bacterial DNA and metabolome in serum

## TL;DR

This study identifies serum bacterial DNA and metabolite profiles that can help distinguish colorectal cancer patients from healthy individuals, offering potential for early diagnosis.

## Contribution

The study introduces serum-based bacterial and metabolomic profiles as novel, non-invasive biomarkers for colorectal cancer diagnosis.

## Key findings

- Serum levels of Firmicutes and threonic acid significantly differentiate colorectal cancer patients from controls.
- Integrated analysis achieved high predictive accuracy (AUC = 0.95) for colorectal cancer diagnosis.
- Results are independent of age, gender, and body mass index, suggesting broad clinical applicability.

## Abstract

There is increasing evidence demonstrating the relationship between microbiota and colorectal cancer. Several studies have been published analyzing microbiota in tissues and feces from cancer patients; however, there are only a few publications investigating the clinical utility of serum microbiome from colorectal cancer patients. Our aim was to advance in the search for serum biomarkers for the diagnosis of colorectal cancer.

We conducted a cross-sectional study assessing bacterial DNA and metabolomic profiles in 64 serum samples from subjects affected by colorectal cancer and controls. A metagenomic analysis of the bacterial 16S rRNA gene in serum was established, and serum metabolites were detected through an untargeted metabolic study based on Gas Chromatography-Quadruple Time-Of-Flight Mass Spectrometry with accurate mass.

After integrating the data resulting from the bioinformatics and statistical analyses, we obtained different profiles in colorectal cancer population and controls, regardless of the subjects' age, gender and body mass index. Serum levels of Firmicutes and threonic acid were the most relevant characteristics that could help differentiate both groups, achieving an excellent predictive accuracy in this discovery cohort (area under the ROC curve = 0.95). Although these results should be validated in other cohorts through multicenter studies, we consider that our data could be relevant and applicable to the early diagnosis of colorectal cancer.