美国斯隆凯特林研究所Marcel R.M. van den Brink课题组完成癌症患者用药、微生物组和死亡率之间关联的高分辨率分析。该研究于2023年6月8日发表于国际一流学术期刊《细胞》。

研究人员通过开发和应用一种新的计算方法PARADIGM（与肠道微生物群动态相关的参数）来解读了药物暴露和微生物组成变化之间的关系，该方法具有详细的用药记录，并且来自接受异基因造血细胞移植病人的纵向粪便微生物组谱。研究人员观察到，一些非抗生素药物，包括泻药、止血药和阿片类药物，与肠球菌相对丰度的增加和α-多样性的减少有关。

霰弹枪元基因组测序进一步证明了亚种竞争，导致同种异体移植期间显性菌株遗传趋同增加，这与抗生素暴露有很大关系。研究人员整合了药物与微生物组的关系，仅凭药物暴露就能预测两个验证队列的临床结果，这表明这种方法可以产生生物和临床相关的见解，并了解药物暴露如何扰乱或保持微生物组的组成。

据悉，辨别药物暴露对癌症患者肠道细菌群落的影响是一个挑战。

附：英文原文

Title: High-resolution analyses of associations between medications, microbiome, and mortality in cancer patients

Author: Chi L. Nguyen, Kate A. Markey, Oriana Miltiadous, Anqi Dai, Nicholas Waters, Keimya Sadeghi, Teng Fei, Roni Shouval, Bradford P. Taylor, Chen Liao, John B. Slingerland, Ann E. Slingerland, Annelie G. Clurman, Molly A. Maloy, Lauren Bohannon, Paul A. Giardina, Daniel G. Brereton, Gabriel K. Armijo, Emily Fontana, Ana Gradissimo, Boglarka Gyurkocza, Anthony D. Sung, Nelson J. Chao, Sean M. Devlin, Ying Taur, Sergio A. Giralt, Miguel-Angel Perales, Joao B. Xavier, Eric G. Pamer, Jonathan U. Peled, Antonio L.C. Gomes, Marcel R.M. van den Brink

Issue&Volume: 2023/06/08

Abstract: Discerning the effect of pharmacological exposures on intestinal bacterial communitiesin cancer patients is challenging. Here, we deconvoluted the relationship betweendrug exposures and changes in microbial composition by developing and applying a newcomputational method, PARADIGM (parameters associated with dynamics of gut microbiota),to a large set of longitudinal fecal microbiome profiles with detailed medication-administrationrecords from patients undergoing allogeneic hematopoietic cell transplantation. Weobserved that several non-antibiotic drugs, including laxatives, antiemetics, andopioids, are associated with increased Enterococcus relative abundance and decreased alpha diversity. Shotgun metagenomic sequencingfurther demonstrated subspecies competition, leading to increased dominant-straingenetic convergence during allo-HCT that is significantly associated with antibioticexposures. We integrated drug-microbiome associations to predict clinical outcomesin two validation cohorts on the basis of drug exposures alone, suggesting that thisapproach can generate biologically and clinically relevant insights into how pharmacologicalexposures can perturb or preserve microbiota composition.

DOI: 10.1016/j.cell.2023.05.007

Source: https://www.cell.com/cell/fulltext/S0092-8674(23)00526-3