Zhu Chengpei, Wang Yunchao, Zhu Ruijuan, Wang Shanshan, Xue Jingnan, Zhang Dongya, Lan Zhou, Zhang Chenchen, Liang Yajun, Zhang Nan, Xun Ziyu, Zhang Longhao, Ning Cong, Yang Xu, Chao Jiashuo, Long Junyu, Yang Xiaobo, Wang Hanping, Sang Xinting, Jiang Xianzhi, Zhao Haitao
Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), No. 1 Shuaifuyuan, Wangfujing, Beijing, 100730, China.
Department of General Surgery Center, Clinical Center for Liver Cancer, Beijing YouAn Hospital, Capital Medical University, Beijing, China.
Biomark Res. 2024 Jun 3;12(1):56. doi: 10.1186/s40364-024-00607-8.
BACKGROUND: Accumulating evidence suggests that the gut microbiota and metabolites can modulate tumor responses to immunotherapy; however, limited data has been reported on biliary tract cancer (BTC). This study used metagenomics and metabolomics to identify characteristics of the gut microbiome and metabolites in immunotherapy-treated BTC and their potential as prognostic and predictive biomarkers. METHODS: This prospective cohort study enrolled 88 patients with BTC who received PD-1/PD-L1 inhibitors from November 2018 to May 2022. The microbiota and metabolites significantly enriched in different immunotherapy response groups were identified through metagenomics and LC-MS/MS. Associations between microbiota and metabolites, microbiota and clinical factors, and metabolites and clinical factors were explored. RESULTS: Significantly different bacteria and their metabolites were both identified in the durable clinical benefit (DCB) and non-durable clinical benefit (NDB) groups. Of these, 20 bacteria and two metabolites were significantly associated with survival. Alistipes were positively correlated with survival, while Bacilli, Lactobacillales, and Pyrrolidine were negatively correlated with survival. Predictive models based on six bacteria, four metabolites, and the combination of three bacteria and two metabolites could all discriminated between patients in the DCB and NDB groups with high accuracy. Beta diversity between two groups was significantly different, and the composition varied with differences in the use of immunotherapy. CONCLUSIONS: Patients with BTC receiving immunotherapy have specific alterations in the interactions between microbiota and metabolites. These findings suggest that gut microbiota and metabolites are potential prognostic and predictive biomarkers for clinical outcomes of anti-PD-1/PD-L1-treated BTC.
背景：越来越多的证据表明，肠道微生物群及其代谢产物可调节肿瘤对免疫治疗的反应；然而，关于胆管癌（BTC）的相关数据报道有限。本研究采用宏基因组学和代谢组学来确定接受免疫治疗的BTC患者肠道微生物群和代谢产物的特征及其作为预后和预测生物标志物的潜力。 方法：这项前瞻性队列研究纳入了88例在2018年11月至2022年5月期间接受PD-1/PD-L1抑制剂治疗的BTC患者。通过宏基因组学和液相色谱-串联质谱法（LC-MS/MS）确定在不同免疫治疗反应组中显著富集的微生物群和代谢产物。探讨了微生物群与代谢产物之间、微生物群与临床因素之间以及代谢产物与临床因素之间的关联。 结果：在持久临床获益（DCB）组和非持久临床获益（NDB）组中均鉴定出显著不同的细菌及其代谢产物。其中，20种细菌和两种代谢产物与生存显著相关。阿克曼菌与生存呈正相关，而芽孢杆菌、乳杆菌目和脯氨酸与生存呈负相关。基于六种细菌、四种代谢产物以及三种细菌和两种代谢产物组合的预测模型均能高精度地区分DCB组和NDB组的患者。两组之间的β多样性显著不同，其组成因免疫治疗的使用差异而有所变化。 结论：接受免疫治疗的BTC患者在微生物群与代谢产物之间的相互作用方面存在特定改变。这些发现表明，肠道微生物群和代谢产物是抗PD-1/PD-L1治疗的BTC临床结局的潜在预后和预测生物标志物。
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