# The best from both disciplines: integrating human and microbial signatures from whole genome sequencing to advance cancer diagnostics

## TL;DR

This review highlights how combining human and microbial DNA analysis in liquid biopsies can improve cancer diagnostics and early detection.

## Contribution

The paper introduces the novel integration of host and microbial cell-free DNA analysis for enhanced liquid biopsy applications.

## Key findings

- Microbial cell-free DNA complements host DNA in liquid biopsies for better cancer detection.
- Machine learning is crucial for integrating multi-view data from host and microbial DNA.
- mcfDNA provides insights into disease-causing microbes and the host microbiome in cancer.

## Abstract

Liquid biopsies are transforming oncology, enabling earlier diagnosis, dynamic treatment guidance, and personalized precision medicine, yet current approaches focusing mainly on circulating host cell-free DNA (cfDNA) neglect crucial information within co-existing microbial cell-free DNA (mcfDNA). This review argues for the combined potential of simultaneously analyzing host and microbial signals from samples like blood, specifically focusing on circulating tumor DNA (ctDNA) as the key host component. While ctDNA analysis is already used to guide treatment decisions, the detection of mcfDNA—although present in smaller amounts compared to total cfDNA—offers a distinct and complementary opportunity to identify disease-causing microbes and investigate the host-associated microbiome in the context of cancer. Leveraging machine learning strategies is essential to integrate these multi-view data sets and realize their full potential for enhancing liquid biopsy applications, particularly in early cancer detection.