TY - JOUR
T1 - Gut microbiota and SCFAs improve the treatment efficacy of chemotherapy and immunotherapy in NSCLC
AU - Yang, Yanping
AU - Ye, Maosong
AU - Song, Yijun
AU - Xing, Wenyu
AU - Zhao, Xing
AU - Li, Yufan
AU - Shen, Jiacheng
AU - Zhou, Jian
AU - Arikawa, Kinji
AU - Wu, Shengdi
AU - Song, Yuanlin
AU - Xu, Nuo
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/12
Y1 - 2025/12
N2 - The role of gut dysbiosis in shaping immunotherapy responses is well-recognized, yet its effect on the therapeutic efficacy of chemotherapy and immunotherapy combinations remains poorly understood. We analyzed gut microbiota in non-small cell lung cancer (NSCLC) patients treated with chemo-immunotherapy, comparing responders and non-responders using 16S rRNA sequencing. Responders showed higher microbial richness and abundance of specific genera like Faecalibacterium and Subdoligranulum, and the phylum Firmicutes. Support vector machine (SVM), a machine learning model based on microbial composition, predicted treatment efficacy with the area under the curve (AUC) values of 0.763 for genera and 0.855 for species. Metagenomic analysis revealed significant differences in metabolic pathways, with responders exhibiting higher short-chain fatty acids (SCFAs) production. Fecal microbiota transplantation (FMT) and SCFAs supplementation in mouse models enhanced treatment efficacy by promoting effector T cell activity in tumors. Our study suggests that gut microbiota, through SCFAs production, regulates chemo-immunotherapy efficacy, offering new strategies to improve NSCLC treatment outcomes.
AB - The role of gut dysbiosis in shaping immunotherapy responses is well-recognized, yet its effect on the therapeutic efficacy of chemotherapy and immunotherapy combinations remains poorly understood. We analyzed gut microbiota in non-small cell lung cancer (NSCLC) patients treated with chemo-immunotherapy, comparing responders and non-responders using 16S rRNA sequencing. Responders showed higher microbial richness and abundance of specific genera like Faecalibacterium and Subdoligranulum, and the phylum Firmicutes. Support vector machine (SVM), a machine learning model based on microbial composition, predicted treatment efficacy with the area under the curve (AUC) values of 0.763 for genera and 0.855 for species. Metagenomic analysis revealed significant differences in metabolic pathways, with responders exhibiting higher short-chain fatty acids (SCFAs) production. Fecal microbiota transplantation (FMT) and SCFAs supplementation in mouse models enhanced treatment efficacy by promoting effector T cell activity in tumors. Our study suggests that gut microbiota, through SCFAs production, regulates chemo-immunotherapy efficacy, offering new strategies to improve NSCLC treatment outcomes.
UR - https://www.scopus.com/pages/publications/105011935257
U2 - 10.1038/s41522-025-00785-9
DO - 10.1038/s41522-025-00785-9
M3 - 文章
C2 - 40721426
AN - SCOPUS:105011935257
SN - 2055-5008
VL - 11
JO - npj Biofilms and Microbiomes
JF - npj Biofilms and Microbiomes
IS - 1
M1 - 146
ER -