AUTHOR=He Xin , Zhao Qing , Zhang Jianhong , Shi Jing , Wan Ningyi , Tang Bin , Tian Bo , Li Pu 

TITLE=Potential and application of Fusobacterium nucleatum in the diagnosis and treatment of colorectal cancer

JOURNAL=Frontiers in Microbiology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2025.1652702

DOI=10.3389/fmicb.2025.1652702

ISSN=1664-302X

ABSTRACT=Colorectal cancer (CRC), as a globally prevalent malignant tumor, relies on in-depth analysis of tumor microenvironment regulation mechanisms for precision diagnosis and treatment. Fusobacterium nucleatum (F. nucleatum), a key carcinogenic bacterium, has been revealed in recent studies to play multidimensional roles in CRC initiation, progression, and metastasis. This review systematically summarizes the progress of Fn applications in CRC full-cycle management: (1) In the diagnostic field, Fn detection technology based on fecal samples has developed into a new non-invasive screening strategy. Cohort studies show its diagnostic performance (AUC 0.82–0.89), with significant correlations to tumor stage (III/IV stage OR = 2.87), lymph node metastasis (HR = 1.94), and reduced 5-year survival rate (35% vs. 62%); (2) For therapeutic monitoring, dynamic Fn load changes can predict chemotherapy (OR = 0.63) and immunotherapy responses (PFS extended by 2.1 months); (3) In prognostic evaluation, metagenomic analysis shows that high Fn abundance is closely related to TNM staging (C-index 0.81 vs. 0.69) and recurrence risk (AUC = 0.88). Notably, a nomogram model integrating Fn biomarkers can improve the predictive accuracy of the traditional TNM staging system by 17.3%. Although existing evidence supports the clinical translational value of Fn, its standardized detection protocols, threshold setting, and targeted intervention strategies (such as antibiotic therapy and phage therapy) still require validation through multi-center prospective studies. This review provides evidence-based medical evidence for the application of Fn in CRC precision medicine by integrating multi-omics data.