Integrated Host Genomics, Microbiome, and Metabolome for Cancer Early Detection, Risk Stratification, Precision Intervention, and Treatment-Response Modeling

Cancer prevention and precision oncology increasingly rely on the integration of multidimensional biological information. Beyond tumor-intrinsic genomic alterations, host genetic background, microbiome composition and function, and systemic or local metabolic remodeling may jointly influence cancer susceptibility, early detection, disease progression, treatment response, and therapeutic resistance. Advances in genomics, metagenomics, metabolomics, proteomics, single-cell technologies, and computational modeling now provide opportunities to move beyond single-biomarker discovery toward integrated, interpretable, and clinically actionable models. However, the mechanisms linking host genomic variation, microbial ecology, metabolite profiles, and cancer-related phenotypes remain incompletely understood. A focused Research Topic is therefore needed to bring together studies that clarify these interactions and translate multi-omics findings into cancer prevention, risk stratification, and precision intervention.This Research Topic aims to address how integrated host genomics, microbiome, and metabolome information can improve cancer early detection, risk prediction, precision intervention, and treatment-response modeling. The central problem is that current cancer risk and therapeutic models often evaluate host molecular alterations, microbial features, metabolic profiles, and clinical phenotypes separately, which limits biological interpretation and clinical utility. By encouraging multi-omics integration and mechanistic interpretation, this collection seeks to promote a more comprehensive framework for understanding cancer initiation, progression, immune modulation, and therapeutic resistance.To achieve this goal, we welcome studies that combine host genetic or genomic data with microbiome and metabolome profiles, ideally linked to clinical outcomes, functional validation, or translational application. The Research Topic will emphasize biologically interpretable models, validated biomarkers, and mechanistic studies that can support early diagnosis, individualized risk assessment, treatment selection, and targeted intervention strategies in cancer.We welcome Original Research, Review, Mini Review, Systematic Review, Methods, Brief Research Report, Perspective, Technology and Code, and Data Report articles. Potential themes include, but are not limited to: • Host genomic determinants of microbiome-associated cancer susceptibility;• Microbiome–metabolome biomarkers for early cancer detection;• Integrated multi-omics models for cancer risk stratification, prognosis, and treatment response;• Microbial metabolites and host pathways shaping the tumor microenvironment, immune regulation, and therapy resistance;• Diet–microbiome–metabolome–host interactions in carcinogenesis;• AI or machine-learning approaches integrating genomic, microbial, metabolic, and clinical data.Studies using longitudinal cohorts, external validation, functional experiments, single-cell or spatial omics, and translational biomarker platforms are particularly encouraged. Submissions should maintain a clear genetics, genomics, or multi-omics focus with relevance to cancer prevention or precision oncology. Topic editors: Hui Li, Yousi Fu, Qiqing Li Source: https://www.frontiersin.org/research-topics/81015/integrated-host-genomics-microbiome-and-metabolome-for-cancer-early-detection-risk-stratification-precision-intervention-and-treatment-response-modeling