微生物群
生物
癌症
免疫疗法
人体微生物群
疾病
结直肠癌
临床试验
粪便细菌疗法
移植
免疫学
生物信息学
癌症免疫疗法
转移
免疫系统
人类微生物组计划
免疫
不利影响
计算生物学
癌症治疗
癌症治疗
器官移植
癌症研究
基因组
肿瘤免疫学
人类疾病
靶向治疗
随机对照试验
精密医学
作者
Hassane M. Zarour,Giorgio Trinchieri
标识
DOI:10.1146/annurev-immunol-082323-114522
摘要
Humans are metaorganisms, composed of both host (human) cells and a roughly equal number of commensal microorganisms-collectively known as the microbiome-residing primarily at epithelial barrier surfaces. This review considers human cancer as a disease of the metaorganism, to which the microbiome contributes by influencing genome stability, tissue organization, inflammation, immunity, tumor initiation and promotion, metastasis formation, and therapeutic response. We summarize evidence demonstrating that machine learning models trained on patients' microbiome features moderately predict clinical response to immunotherapy and the development of immune-related adverse events. We review results from single-arm and randomized clinical trials wherein fecal microbiome transplantation from therapy-responsive patients or healthy donors, when combined with therapy targeting programmed cell death 1 (PD-1), improved outcomes in PD-1-refractory patients or served as an effective first-line intervention. We conclude by highlighting the emerging opportunities and ongoing challenges in leveraging the microbiome to enhance the efficacy and safety of cancer immunotherapy.
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