Exploring the gut microbiome and immunological landscape in kidney cancer: a Mendelian randomization analysis - Lv, Shihui; Guo, Qian; He, Yuhan; Yu, Zhixian; Zhan, Xianjing; Li, Hang; Pan, Yue (Frontiers in Immunology, 2024)
Introduction Kidney cancer (KC) is a significant health burden globally, with over 400,000 new cases estimated in 2020. The prognosis of KC is influenced by various factors, including tumor spread, pathological characteristics, and molecular genetic changes. Recent studies have emphasized the involvement of gut microbiota and the immune system’s contribution in the onset of KC. This extensive research endeavor sought to investigate the potential associations between diverse immune cell phenotypes, specific gut microbiota species, and their impact on the risk of developing KC, alongside the examination of circulating inflammatory proteins. Methods Adhering to the STROBE-MR guidelines, our investigation involved a two-stage Mendelian randomization (2SMR) analysis grounded on three fundamental assumptions: relevance, independence, and exclusion restriction. The exposure data utilized in this study originated from genome-wide association studies (GWAS) specifically designed to explore immune traits, inflammatory proteins, and gut microbiota compositions. Results Our analysis identified 25 immune phenotypes, 4 circulating inflammatory proteins, and 12 gut microbiota features that exhibited significant causal associations with KC (P < 0.05). 10 immune phenotypes were protective against KC, while 15 were risk factors. Among the inflammatory proteins, CCL28 and IL-2 were protective, whereas FGF-23 and β-NGF were risk factors. Gut microbiota features associated with reduced KC risk included biosynthetic pathways involving amino acids and specific bacterial genera, whereas others, like Butyrivibrio crossotus and Odoribacter splanchnicus, were risk factors. Conclusion Immune, inflammatory, and gut microbiota factors impact KC development. Identified factors hint at biomarkers and therapeutic targets. It is very important to understand the relationship between these factors and KC.