Intestinal Microbiome Associated With Immune-Related Adverse Events for Patients Treated With Anti-PD-1 Inhibitors, a Real-World Study

FRONTIERS IN IMMUNOLOGY(2021)

引用 21|浏览2
暂无评分
摘要
AimImmune checkpoint inhibitors (ICIs) have updated the treatment landscape for patients with advanced malignancies, while their clinical prospect was hindered by severe immune-related adverse events (irAEs). The aim of this study was to research the association between gut microbiome diversity and the occurrence of ICI-induced irAEs. Patients and MethodWe prospectively obtained the baseline fecal samples and clinical data from patients treated with anti-PD-1 inhibitors as monotherapy or in combination with chemotherapy or antiangiogenesis regardless of treatment lines. The 16S rRNA V3-V4 sequencing was used to test the gene amplicons of fecal samples. The development of irAEs was evaluated and monitored from the beginning of therapy based on CTCAE V5.01. ResultsA total of 150 patients were included in the study and followed up for at least 6 months. A total of 90 (60%) patients developed at least one type of adverse effect, among which mild irAEs (grades 1-2) occurred in 65 patients (72.22%) and severe irAEs (grades 3-5) in 25 patients (27.78%). Patients with severe irAEs showed a visible higher abundance of Streptococcus, Paecalibacterium, and Stenotrophomonas, and patients with mild irAEs had a higher abundance of Faecalibacterium and unidentified_Lachnospiraceae. With the aid of a classification model constructed with 5 microbial biomarkers, patients without irAEs were successfully distinguished from those with severe irAEs (AUC value was 0.66). ConclusionCertain intestinal bacteria can effectively distinguish patients without irAEs from patients with severe irAEs and provide evidence of gut microbiota as an informative source for developing predictive biomarkers to predict the occurrence of irAEs.
更多
查看译文
关键词
gut microbiome, PD-1, PD-L1, immune-related adverse effects, interindividual difference
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要