ArticleNeurosurgical review2025
Unveiling gut microbiome divergence in sellar-parasellar masses and brain tumors: A link beyond the skull.
Article in Neurosurgical review, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The gut microbiome is increasingly linked to systemic health and central nervous system disorders, including brain tumors. This study investigated gut microbiome composition and metabolic profiles in patients with sellar-parasellar tumors (SPTs), other brain tumor types (OBTs) and healthy controls (HCs) to identify microbial and metabolic biomarkers for brain tumor phenotypes. A cross-sectional study involving 56 participants (17 SPTs, 11 OBTs, 28 HCs) was conducted. Gut microbiota composition was analyzed with 16 S rRNA sequencing, and metabolic activity was inferred via metagenome-scale metabolic models. Multivariable regression and machine learning were used to evaluate microbial and metabolic differences across groups. Taxonomic and metabolic analyses revealed distinct profiles across these groups. The result showed that HCs exhibited higher levels of Lachnospira and Comamonadaceae, while tumor patients had an over-representation of Bacilli. OBT patients showed elevated metabolic exchange scores (MES) for amino acids (D-alanine, L-glutamic acid), carbohydrates (mucin-type O-glycans, alpha-lactose), and lipids (stearic acid, choline), most likely reflecting tumor-associated metabolic demands. Conversely, SPT patients had profiles closer to HCs, with lower MES and reduced systemic disruption. Key taxa such as Akkermansia, Faecalibacterium, and Lachnospira demonstrated tumor-specific adaptive metabolic outputs, emphasizing functional microbial contributions over purely taxonomic roles. These findings highlight the role of gut microbiota in brain tumor progression through altered metabolic pathways, suggesting potential biomarkers and therapeutic targets for neuro- oncology. The study integrates genome-scale metabolic modeling with 16 S profiling to show that functional metabolic divergence can exist even when taxonomic differences are subtle, revealing overlooked biomarkers of the gut-brain axis in neuro-oncology.
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