Unraveling the Ecological Mechanisms Influencing the Structure and Composition of Lung Cancer Microbiomes

This study investigates the ecological mechanisms governing the structure and composition of lung microbiome communities within tumor tissue from lung cancer patients. While this field has attracted increasing research attention, the ecological and etiological mechanisms driving microbial community assembly in this environment remain poorly characterized. To address this gap, we applied Sloan's near neutral model, Ning et al.'s normalized stochasticity ratio framework and Harris et al.'s multi-site neutral model to evaluate the influences of stochastic and deterministic factors at species, community and metacommunity levels, respectively. Our findings include: (i) Stochastic drift exhibited predominant influence at both species and community levels in normal adjacent tissue (NT), exceeding its effects in LUAD (lung adenocarcinoma) and LUSC (lung squamous cell carcinoma). (ii) At the metacommunity level, neutrality was not rejected at the metacommunity or local community levels, which is consistent with the previous finding (i). (iii) Elevated metacommunity biodiversity (θ) and immigration rates (m) in LUAD/LUSC compared to NT (observed in ∼50% of cases) suggest that tumor occurrence/progression may actively promote microbial recruitment to tumor microenvironments. We propose three non-exclusive mechanistic interpretations: (i) Tumor-mediated immune modulation creates permissive ecological niches; (ii) structural remodeling of tissue enhances microbial colonization potential; (iii) selective enrichment of opportunistic taxa (e.g., Streptococcus) through tumor-specific microenvironmental changes. Our results demonstrate that LUAD and LUSC microbiomes are shaped by deterministic tumor-driven selection, in contrast to the predominantly stochastic assembly observed in NT microbiomes. These findings reveal substantial reorganization of tumor-associated microbial communities, warranting further biomedical investigation and clinical validation.