Abstract
BACKGROUND: The mycobiome in the tumor microenvironment of non-smokers with early-stage lung adenocarcinoma (ES-LUAD) has been minimally investigated. METHODS: In this study, we conducted ultra-deep metagenomic and transcriptomic sequencing on 128 samples collected from 46 nonsmoking ES-LUAD patients and 41 healthy controls (HC), aiming to characterize the tumor-resident mycobiome and its interactions with the host. RESULTS: The results revealed that ES-LUAD patients exhibited fungal dysbiosis characterized by reduced species diversity and significant imbalances in specific fungal abundances. Concurrently, microbial functional analysis revealed significant alterations associated with genes such as ribosomal proteins and histones. We observed correlations between Yarrowia lipolytica, Saccharomyces paradoxus, and tumor-infiltrating immune cells (TIICs), and identified a strong association (|rho| > 0.7) between S. paradoxus and 14 transcription factors. A signature of three prognostic genes (GRIA1, CDO1, FHL1) closely associated with S. paradoxus was identified and they suggest that the interaction between the mycobiome and the host may contribute to prolonged overall survival (OS). Finally, a predictive model based on six fungi demonstrated decent classification performance in distinguishing ES-LUAD cases from HCs (AUC = 0.724). CONCLUSIONS: Our study demonstrates that the interactions between the mycobiome and transcriptome within tumors may help elucidate the pathogenic mechanisms of ES-LUAD. Fungi, as a potential predictive tool, can be used as an additional resource for accurately detecting and discriminating individuals with ES-LUAD.