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

作者：Xiaoqian Shi, Nan Bi, Wenyang Liu, Liying Ma, Mingyang Liu, Tongzhen Xu, Xingmei Shu, Linrui Gao, Ranjiaxi Wang, Yinan Chen, Li Li, Yu Cheng Zhu, Dan Li · 发表于：Pathogens · 年份：2025 · DOI：10.3390/pathogens14121294 · 被引用次数：1 · 研究领域：Oral microbiology and periodontitis research、Gut microbiota and health、Oral health in cancer treatment

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...