Microbiome-Driven Immunomodulation in Cancer: From Gut Bacteria to Personalized Immunotherapy
DOI:
https://doi.org/10.65761/pjcr.2026.58Keywords:
Microfluidic chip, Gut microbiome, Cancer immunotherapy, organ-on-a-chip, precision oncologyAbstract
Background: Cancer progression and therapeutic response are influenced by tumor biology, host immunity, genetics, and the gut microbiome. Increasing evidence indicates that microbial composition and metabolites can modify inflammation, immune signaling, drug metabolism, and responses to cancer immunotherapy.
Objective: This review examines the role of the microbiome in cancer biology and immunotherapy and evaluates emerging engineering and computational technologies for investigating microbiome–immune–tumor interactions and supporting personalized therapeutic strategies.
Methods: Relevant evidence was synthesized across studies addressing microbiome–cancer interactions, microbiome–drug metabolism, stem cell-derived extracellular vesicles, organ-on-a-chip systems, tumor-on-a-chip platforms, microfluidic technologies, and in silico approaches. Particular emphasis was placed on physiologically relevant models capable of integrating microbial, immune, tumor, and therapeutic components.
Results: Gut microorganisms and their metabolites may influence tumor-associated inflammation, immune activation, epithelial integrity, drug metabolism, and immunotherapy response. Gut-on-a-chip and tumor-on-a-chip platforms can reproduce selected physiological and pathological features, including fluid flow, oxygen gradients, tissue interfaces, immune-cell interactions, and microbial signaling. Microfluidic systems further enable controlled co-culture, real-time monitoring, high-throughput screening, and assessment of therapeutic responses. Computational approaches, including molecular docking, molecular dynamics, protein-structure prediction, protein–protein interaction analysis, and machine learning, provide complementary tools for identifying therapeutic targets and predicting treatment responses.
Conclusion: Integrated microbiome engineering, microfluidics, organ-on-a-chip technologies, and computational approaches provide promising platforms for mechanistic cancer research, drug screening, and precision immunotherapy. However, standardization, scalability, regulatory requirements, reproducibility, and multicenter clinical validation remain important barriers to translation. Future integration with artificial intelligence, microbiome engineering, and patient-specific models may further advance individualized cancer treatment.
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