Novel screening approach for cancer cachexia using metagenomic gut microbiome profiling in patients with advanced non-small cell lung cancer.

12090 Background: Cancer cachexia (CC) is a multifactorial syndrome involving immune-metabolic crosstalk across multiple organs and has been associated with a negative clinical impact in patients with non-small cell lung cancer (NSCLC) amenable to immune checkpoint inhibitors (ICIs). In parallel, the gut microbiome (GM) has emerged as a key contributor to ICI response. In this study, we aimed to evaluate the association between CC and GM composition and its metabolic potentials. Methods: We collected fecal samples from 139 patients with advanced NSCLC treated with ICI. In addition to 16S rRNA sequencing for all patients, shotgun metagenomic microbiome profiling was performed for 69 patients to estimate the species-level composition and functional capacity of the GM. Cancer cachexia was diagnosed according to the international consensus based on the body weight changes over the previous six months. Survival time was calculated using the Kaplan-Meier method. GM diversity indices, differential abundance, and functional profiles based on the MetaCyc database were compared between the patients with and without CC. Results: Median progression-free survival (PFS) and overall survival (OS) were significantly shorter in the cachexia group compared to the non-cachexia group 4.5 vs. 11.5 months (p < 0.001) and 10.8 vs. 44.9 months (p < 0.01), respectively. Both GM profiling techniques revealed a significant difference in beta diversity between both groups (p < 0.01). In addition, metagenomic analyses revealed the distinct characteristics of GM at the species level between the groups. The CC group showed an overrepresentation of the commensal bacteria, such as Escherichia coli, Ruthenibacterium lactatiformans, Hungatella hathewayi,and Eggerthella lenta, whereas the non-CC group showed an enrichment of Parabacteroides distasonis, Eubacterium rectale,and Roseburia inulinivorans. Moreover, functional analysis revealed the significantly different metabolic potentials of GM in the CC group. The CC group showed an enrichment of pathways, such as D-arabinose degradation II, L-lysine degradation, and octan oxidation. Finally, the clustering of patients based on significant metabolic pathways or gene reactions provided a high predictive ability to discriminate between patients with and without CC. Conclusions: The shotgun metagenomic approach allowed for the characterization of the altered gut microbes and their metabolic potentials in patients with CC. Stratification based on the GM profiles may be useful as a novel screening method for CC, which is progressive and may involve more multistage pathology than identified by the conventional approach.