生物
肠道菌群
微生物学
免疫疗法
癌症
计算生物学
癌症免疫疗法
免疫学
遗传学
作者
Xiaowen Huang,Muni Hu,Tiantian Sun,Jiantao Li,Yilu Zhou,Yuqing Yan,Baoqin Xuan,Jilin Wang,Hua Xiong,Linhua Ji,Xiaoqiang Zhu,Tianying Tong,Lijun Ning,Yanru Ma,Ying Zhao,Jinmei Ding,Zhigang Guo,Youwei Zhang,Jing‐Yuan Fang,Jie Hong
标识
DOI:10.1016/j.chom.2023.10.005
摘要
The effect of gut bacteria on the response to immune checkpoint inhibitors (ICIs) has been studied, but the relationship between fungi and ICI responses is not fully understood. Herein, 862 fecal metagenomes from 9 different cohorts were integrated for the identification of differentially abundant fungi and subsequent construction of random forest (RF) models to predict ICI responses. Fungal markers demonstrate excellent performance, with an average area under the curve (AUC) of 0.87. Their performance improves even further, reaching an average AUC of 0.89 when combined with bacterial markers. Higher enrichment of exhausted T cells is detected in responders, as predicted by fungal markers. Multi-kingdom network and functional analysis reveal that the fungus Schizosaccharomyces octosporus may ferment starch into short-chain fatty acids in responders. This study provides a fungal profile of the ICI response and the identification of multi-kingdom microbial markers with good performance that may improve the overall applicability of ICI therapy.
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