Microbiome–Metabolome Crosstalk in HPV Pathogenesis: From Ecosystem Dynamics to Translational Biomarkers
Abstract
High-risk human papillomavirus (hrHPV) infection alters the cervicovaginal microenvironment, driving metabolic reprogramming that influences viral persistence and progression to cervical cancer. This review adopts a systems-level perspective to synthesize findings from recent metabolomic studies across urine, vaginal swabs, and cervicovaginal fluids, highlighting consistent trends from cervicovaginal health through hrHPV infection, persistence, cervical lesion development, and cancer. HPV infection is characterized by increased microbial amines and oxidative stress, whereas viral persistence and high-grade cervical lesions exhibit disrupted metabolism of amino acids, lipids, and nucleotides. Cervical cancer is associated with distinct metabolic signatures involving sphingolipids, ketone bodies, and intermediates of the tricarboxylic acid cycle. Collectively, metabolic profiles emerge as functional readouts of host-microbiome interactions, often showing stronger associations with clinical outcomes than microbial composition alone. Integrative multiomics approaches combining metabolomics with microbiome- and host-derived data are beginning to uncover coordinated biological pathways underlying HPV pathogenesis and may improve risk stratification and biomarker discovery. Despite methodological heterogeneity, converging evidence supports the potential of metabolic profiling for early detection of cervical neoplasia and stratification of hrHPV-positive women, although reproducibility across studies remains limited. Future longitudinal and integrative studies, supported by standardized analytical frameworks and computational modeling, are needed to clarify causal mechanisms and enable the development of clinically actionable biomarkers and targeted interventions.
Fields of Study & Subjects
Reproductive tract infections research
Biological Research and Disease Studies
Cervical Cancer and HPV Research
Publication details
- Journal / source
- Computational and Structural Biotechnology Journal
- Publisher
- American Association for the Advancement of Science (AAAS)
- Volume
- 35
- Issue
- 1
- Pages
- 0158–0158
- Publication date
- 1 March 2026
- Language
- EN