Lung Tissue Microbiome in NSCLC Patients: Metabarcoding Analysis Identifies Escherichia-Shigella as an Abundant Taxon

Background: Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality worldwide despite advances in diagnosis and treatment. Increasing evidence suggests that alterations in the lung microbiome may contribute to NSCLC development and progression; however, findings remain inconsistent due to heterogeneous biological materials and methodological differences among studies. Therefore, this study aimed to characterize the lung tissue microbiome in NSCLC using a paired tissue-based approach. Methods: Thirty-two patients with NSCLC were enrolled. For each patient, two samples were collected: primary tumor tissue and matched macroscopically unchanged adjacent lung tissue. The V3-V4 region of the 16S rRNA gene was amplified and sequenced, followed by bioinformatic analysis using the QIIME2 pipeline. Results: Tumor tissues demonstrated lower alpha (Shannon H = 9.60, q = 0.001) and beta (Jaccard pseudo-F = 1.26, q = 0.015) diversity compared with adjacent controls, indicating reduced microbial complexity within the tumor microenvironment. Escherichia-Shigella was the most abundant detected genus (~12%) in both groups, although without a statistically significant difference. Analysis of microbiome variation in relation to spatial distance between sampled tissues revealed a strong trend toward significance (p = 0.07) with a substantial effect size (R² = 0.207). Conclusions: The observed microbiome alterations in NSCLC were more evident at the ecological level than in overall taxonomic composition, supporting a model of microbial community simplification rather than complete compositional replacement. Our findings also suggest that tumor-adjacent lung tissue may not represent a fully neutral control due to the local field effect. The relatively high abundance of Escherichia-Shigella indicates that this taxon may warrant further investigation in NSCLC microbiome studies.