Integrative systems-level analysis identifies potential gut microbial metabolite-host signaling networks in lung adenocarcinoma.
TL;DR
A systems biology approach integrating gut microbial metabolite annotation, metabolite-associated gene identification, transcriptomics validation, network topology analysis, immune infiltration profiling, and single-cell transcriptomic datasets to investigate potential metabolite-host interactions associated with lung adenocarcinoma (LUAD).
Abstract
The gut microbiome has emerged as a potential modulator of the immune system, host metabolism, and cancer progression; however, the effects of microbiota-derived metabolites on distal lung cancer remain poorly understood. The current study adopts a systems biology approach integrating gut microbial metabolite annotation, metabolite-associated gene identification, transcriptomics validation, network topology analysis, immune infiltration profiling, and single-cell transcriptomic datasets to investigate potential metabolite-host interactions associated with lung adenocarcinoma (LUAD). The novelty of this study lies in integrating gut microbial metabolites with types of host molecular data to systematically prioritize and orient candidate metabolite-host genes and pathways interactions associated with LUAD. A total of 458 metabolites annotated as microbiota-associated and/or host-microbe co-metabolites were found to be enriched in amino acid, pyrimidine, and central carbon metabolic pathways. Integration of metabolite-associated genes with LUAD-related differentially expressed genes identified 603 overlapping targets enriched in cancer-associated pathways, including PI3K/Akt signaling, cytokine-cytokine receptor interaction, focal adhesion, and extracellular matrix receptor interaction. Network topology analysis prioritized SPP1 as a central hub gene. Independent validation in GSE31210 showed association of elevated SPP1 expression with reduced overall survival (log-rank p = 0.0007). Further, correlation analysis exhibited a positive association between SPP1 and GREM1 (ρ = 0.639, FDR = 1.76 × 10⁻¹⁷). Gene-metabolite interaction mapping identified multiple SPP1-associated metabolites, with oxalic acid prioritized for further investigation. Immune infiltration and single-cell analyses further associated SPP1 with macrophage-rich and stromal compartments of the LUAD tumor microenvironment (TME). Collectively, integration of 458 metabolites and 603 candidate genes prioritized an oxalic acid-SPP1-associated network with prognostic and TME relevance in LUAD, providing testable candidates for subsequent experimental validation.