Integrative Analysis of Multiomic Pathways Predicts Cancer-Affected Lobes in Lung Cancer

多组学通路整合分析预测肺癌癌变肺叶

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Abstract

Lung cancer is the leading cause of cancer-related deaths. The human microbiome plays an important role in regulating response to cancer therapeutics, outcomes, and biological processes. However, little is known about the interplay between the lung microbiome and other biological processes in cancer. In an exploratory pilot study, we collected bronchoalveolar lavage fluid and brushings from 20 patients with early-stage lung cancer and performed microbial sequencing, untargeted metabolomics, and cytokine analysis. In addition, we employed computational and machine learning approaches to identify integrated microbial-immunometabolic pathways. Finally, we performed preliminary mechanistic studies to confirm our findings. Previously, we published that upper airway microbiota were selectively enriched in tumor-affected lobes. In the present study, we demonstrate that enrichment of protumorigenic cytokines and specific fatty acids is associated with tumor-affected lobes. Finally, we find that long-chain fatty acid stimulation of macrophages leads to neoplastic transformation of lung epithelial cells. Therefore, the findings of this study identify a perturbed fatty acid-macrophage axis that is a potential biomarker of early-stage lung cancer and will lead to the development of novel therapeutic agents. PREVENTION RELEVANCE: This study identifies a lung microbiome-driven immunometabolic axis involving stearic acid and MIP1β in tumor-affected lobes of patients with early-stage lung cancer. These localized microbial and cytokine-metabolite signatures may serve as biomarkers for early detection and provide targets for preventive strategies in high-risk individuals undergoing lung cancer screening.

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