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DOI 10.1016/j.gendis.2026.102345

Медицинская библиотека · Genes & diseases · 2026

Spatiotemporal dynamics of the host-tumor metabolic interface: Implications for precision nutritional oncology.

Li Mao, Huang Canhua, Yu Shuguang

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Beyond somatic initiation, cancer progression is governed by a multidimensional systemic metabolic architecture. This permissive macroenvironment, shaped by systemic nutrient fluxes, endocrine networks, and microbial co-metabolites, sustains tumor bioenergetics and immune evasion. Bridging the current translational gap requires decoding the spatiotemporal reciprocity between diet-induced metabolic shifts, tumor microenvironment plasticity, and genotoxic therapy responses. In this review, we deconstruct the host-tumor metabolic interface through a systems biology framework, tracing the biotransformation of macro-dietary inputs into subcellular oncogenic and immunological signals. We move beyond traditional nutritional epidemiology to define a precision nutritional oncology paradigm that leverages high-resolution multi-omic biomarkers to track real-time systemic flux, the spatial ecosystem of the microbiome as a localized metabolic bioreactor, and context-dependent metabolic regulation to exploit transient tumor vulnerabilities. We emphasize the need for precise spatiotemporal calibration, particularly during acute refeeding windows, to prevent paradoxical therapy resistance or accelerated cachexia. Finally, we envision a future in which precision nutrition is seamlessly integrated into oncologic care, powered by artificial intelligence and digital gut twins for in silico modeling. By incorporating the broader chemical exposome and addressing structural socioeconomic determinants through frameworks such as the Planetary Health Diet, we outline a roadmap toward global health equity and enhanced metabolic resilience in cancer survivorship.

Для цитирования: Li Mao, Huang Canhua, Yu Shuguang. Spatiotemporal dynamics of the host-tumor metabolic interface: Implications for precision nutritional oncology.. Genes & diseases. 2026. DOI: 10.1016/j.gendis.2026.102345.
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