Gut microbiota and metabolite signatures predict severe immune-related adverse events in advanced hepatobiliary cancers

Sep 23, 2026

Immune checkpoint inhibition in hepatobiliary cancers improves outcomes but immune-related adverse events (irAEs) remain a major safety concern, and the gut microbiome links to ICI efficacy. This study compares patients with severe irAEs versus mild or none, identifying multi-kingdom gut microbiota, fungi, and metabolite signatures. Using metagenomic, ITS2, and metabolomic datasets from 168 advanced patients, severe irAEs associate with longer overall survival, compositional shifts, and a predictive model achieving high discrimination accuracy, highlighting microbiota–fungi–metabolite interaction changes for risk prediction and prognosis.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages13

Reading Time33 min

AccessFree to download

Introduction

Objectives

Methods

Results

Conclusion

Journal of Advanced Research 83 (2026) 775–787 Contents lists available at ScienceDirect Journal of Advanced Research journal [homepage: www. elsevier. com/locate/jare](homepage: www. elsevier. com/locate/jare) | Gut microbiota and metabolite signatures predict severe
immune-related adverse events in advanced hepatobiliary cancers | | | | --- | --- | --- | | Chengpei Zhu a,b, 1, Dongya Zhang c, 1, Yunchao Wang a,d, 1, Chenchen Zhang c, 1, Shanshan Wang a,
Jingnan Xue a, Zhou Lan c, Ziyu Xun a, Longhao Zhang a, Jiashuo Chao a, Yajun Liang c, Wenbin Xue c, Zilun Pu c, Taifeng Zhu a, Cong Ning a, Xinting Sang a, Hanping Wang a,e,⁎⁎, Xianzhi Jiang c,⁎, Xiaobo Yang a,⁎, Haitao Zhao a,⁎
a 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), Beijing, China
b Department of General Surgery Center, Beijing YouAn Hospital, Clinical Center for Liver Cancer, Capital Medical University, Beijing, China c Microbiome Research Center, Moon (Guangzhou) Biotech Ltd., Guangzhou, China
d Organ Transplantation Center, The First Afﬁliated Hospital of Shandong First Medical University, Jinan, China
e Division of Pulmonary and Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College (CAMS & PUMC), Beijing, China | | | | h i g h l i g h t s
• Patients with severe irAEs showed differences in bacterial and metabolite composition.
• Severe irAEs associated with signiﬁcantly longer progression-free/ overall survival.
• Predictive model simultaneously discriminated irAE-Severe from irAEMild and irAE-No.
• Gut microbiota-and/or metabolitebased algorithms could predict severe irAE.
• The research holds promise for offering more accurate predictions and intervention strategies for clinical practice and patient management. | g r a p h i c a l a b s t r a c t
| | a r t i c l e i n f o Article history: Received 14 September 2024 Revised 14 July 2025 Accepted 11 August 2025 Available online 12 August 2025 Keywords: Immune-related adverse event Gut microbiota a b s t r a c t Introduction: Immune checkpoint inhibition (ICI) has proven to be a major breakthrough in hepatobiliary cancers treatment. However, immune-related adverse events (irAEs) remain a major concern. The gut microbiome has been implicated in ICI efﬁcacy; however, speciﬁc alterations in the multi-kingdom gut microbiota associated with severe irAEs are not well understood. Objectives: We aimed to identify the signatures of gut microbiota, fungi, and metabolites in patients with advanced hepatobiliary cancers with severe irAEs compared to those in patients experiencing mild or no irAEs. Methods: We enrolled 168 patients with advanced hepatobiliary cancers between June 2018 and June 2022 (72 in the train set, 31 in test set 1, and 65 in test set 2). Multi-kingdom microbiota proﬁles were investigated ⁎ Corresponding authors. ⁎⁎ Corresponding author at: 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), Beijing, China. E-mail [addresses:](addresses: wanghp@pumch.cn)[ wanghp@pumch.cn](addresses: wanghp@pumch.cn) (H. Wang), [jxz@moonbio.com](jxz@moonbio.com) (X. Jiang), [yangxiaobo67@pumch.cn](yangxiaobo67@pumch.cn) (X. Yang), [zhaoht@pumch.cn](zhaoht@pumch.cn) (H. Zhao). 1 These authors contributed equally. [https://doi.org/10.1016/j.jare.2025.08.016](https://doi.org/10.1016/j.jare.2025.08.016) 2090-1232/© 2025 The Author(s). Published by Elsevier B.V. on behalf of Cairo University. This is an open access article under the CC BY-NC-ND license ([http://creativecommons.org/licenses/by-nc-nd/4.0/](http://creativecommons.org/license

FAQs

What was the main objective of the study?

To identify signatures of gut microbiota, fungi, and metabolites associated with severe irAEs in advanced hepatobiliary cancers, compared with mild or no irAEs.

How were patients grouped in the analysis?

Patients with advanced hepatobiliary cancers were enrolled and categorized as having severe irAEs, mild irAEs, or no irAEs, with train and test sets used for model development and evaluation.

What predictors did the study propose for severe irAEs?

A predictive model based on four bacterial and six metabolite features simultaneously discriminated severe irAEs from mild and no irAEs, suggesting gut microbiota- and/or metabolite-based algorithms for prediction and prognostic markers.

Sep 23, 2026

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