Identification of Oral Microbiome Biomarkers Associated with Lung Cancer Diagnosis and Radiotherapy Response Prediction

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The oral cavity acts as the anatomical gateway to the respiratory tract, sharing both microbiological and pathophysiological links with the lower airways. Although radiotherapy is a cornerstone treatment for lung cancer, reliable oral microbiome biomarkers for predicting patient outcomes remain lacking. We analyzed the oral microbiome of 136 lung cancer patients and 199 healthy controls across discovery and two validation cohorts via 16S rRNA sequencing. Healthy controls exhibited a significantly higher abundance of Streptococcus compared to patients (p = 0.049, p < 0.001, p < 0.001, respectively). The structure of the microbial community exhibited substantial dynamic changes during treatment. Responders showed enrichment of Rothia aeria (p = 0.027) and Prevotella salivae (p = 0.043), associated with prolonged overall survival (OS) and progression-free survival (PFS), whereas non-responders exhibited elevated Porphyromonas endodontalis (p = 0.037) correlating with shorter OS and PFS. According to Analysis of Compositions of Microbiomes with Bias Correction 2 (ANCOM-BC2) analysis, Akkermansia and Alistipes were nearly absent in non-responders, while Desulfovibrio and Moraxella were virtually absent in responders. A diagnostic model based on Streptococcus achieved area under the curve (AUC) values of 0.85 (95% CI: 0.78–0.91) and 0.99 (95% CI: 0.98–1) in the validation cohorts, and a response prediction model incorporating Prevotella salivae and Neisseria oralis yielded an AUC of 0.74 (95% CI: 0.58–0.90). Furthermore, in small cell lung cancer, microbiota richness and diversity were inversely correlated with Eastern Cooperative Oncology Group (ECOG) performance status (p = 0.008, p < 0.001, respectively) and pro-gastrin-releasing peptide (ProGRP) levels (p = 0.065, p = 0.084, respectively). These results demonstrate that lung cancer-associated oral microbiota signatures dynamically reflect therapeutic response and survival outcomes, supporting their potential role as non-invasive biomarkers for diagnosis and prognosis.

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