# Microbiome–Genome Crosstalk in Colorectal Cancer: Colibactin Signatures and Fusobacterium nucleatum in Epidemiology, Driver Selection, and Translation

## TL;DR

This paper explores how bacteria in the gut, like E. coli and Fusobacterium nucleatum, contribute to colorectal cancer through specific genetic changes and how these insights can improve cancer detection and treatment.

## Contribution

The study introduces new evidence linking colibactin and Fusobacterium nucleatum to specific mutational patterns in colorectal cancer and proposes translational applications for precision oncology.

## Key findings

- Colibactin produces specific mutational signatures (SBS88 and ID18) in colorectal cancer and normal colonic crypts.
- Colibactin contributes to APC driver mutations in pks+ E. coli-positive cancers, with geographic and age-related variations.
- Fusobacterium nucleatum influences tumor response to therapy and may affect resistance or sensitivity to anti-PD-1 in MSS CRC.

## Abstract

Colibactin, a genotoxin produced by pks+ E. coli, imprints highly specific mutational signatures SBS88 and ID18 in colorectal cancer (CRC) and even in normal colonic crypts. Population-scale analyses show these signatures are enriched in early-onset CRC, vary geographically, and are imprinted early during tumor evolution, where probabilistic attribution indicates that colibactin contributes to a measurable fraction of APC driver mutations in colibactin-positive cancers. Beyond colibactin, Fusobacterium nucleatum exerts clade-specific effects on tumor ecology and therapy response, with data supporting both chemoresistance and sensitization to anti-PD-1 in microsatellite stable (MSS) CRC. This article covers mechanistic, genomic, and molecular epidemiology evidence, outlines analytic standards for signature detection (whole-genome sequencing (WGS)/whole-exome sequencing (WES), single-sample fitting, and limits at low mutation counts), and charts translational paths spanning noninvasive screening (stool metagenomics + mutational signatures in tissue/circulating tumor DNA (ctDNA)), risk stratification, and microbial-targeted interventions (antibiotics, phages, ClbP inhibitors). Framing microbiome–genome crosstalk as a tractable axis enables testable clinical hypotheses for precision oncology.