Deciphering the Potential Causal and Prognostic Relationships Between Gut Microbiota and Brain Tumors: Insights from Genetics Analysis and Machine Learning

Abstract

The concept of the microbiota-gut-brain axis has witnessed significant advancements, and observational studies revealed dysbiosis in the gut microbiota of patients with brain tumors. The causal relationship between gut microbiota and brain tumors and the potential prognostic value of microbiota are still unclear. Based on multiple Mendelian randomization analyses, this study confirms the causal effects of four gut microbes on meningioma, seven gut microbes on pituitary tumor, and eight gut microbes on glioma. Based on the Sherlock framework, this study identifies 103 meningioma-related microbe-related genes (MRGs), 40 pituitary tumor-related MRGs, and 63 glioma-related MRGs expressed in brain tissues. Almost all glioma-related MRGs are associated with tumor grade and prognosis. Lastly, the prognostic model based on machine learning and microbiota established in this study, namely microbe-related signature (MRS), could robustly predict the prognosis of glioma and provide insights for immunotherapy benefits. This study presents evidence of the causal effects of gut microbes on brain tumors, which contributes to our understanding of the microbiota-gut-brain axis. The relationship between glioma-related MRGs and glioma prognosis, along with the prognostic prediction capacity of MRS and its association with immunotherapy, provides support for the use of gut microbiota as biomarkers to evaluate the prognosis and treatment response of glioma.

Keywords

glioma / gut microbiota / machine learning / mendelian randomization / meningioma / prognosis

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