Multikingdom and functional gut microbiota markers for cholangiocarcinoma.
9 affiliations
- 1Department of Infectious Diseases, State Key Laboratory of Antiviral Drugs, Pingyuan Laboratory, The First Affiliated Hospital of Zhengzhou University, 1#, Jianshe East Road, Zhengzhou, 450052, China.
- 2Gene Hospital of Henan Province/Precision Medicine Center, the First Affiliated Hospital of Zhengzhou University, 1#, Jianshe East Road, Zhengzhou, 450052, China.
- 3Health Management Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
- 4Department of Hepatobiliary and Echinococcosis Surgery, Digestive and Vascular Surgery Center, First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, China.
- 5State Key Laboratory for Diagnosis and Treatment of Infectious Disease, National Clinical Research Center for Infectious Diseases, Department of Infectious Diseases, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, China.
- 6Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450000, China.
- 7Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China. [email protected].
- 8Department of Infectious Diseases, State Key Laboratory of Antiviral Drugs, Pingyuan Laboratory, The First Affiliated Hospital of Zhengzhou University, 1#, Jianshe East Road, Zhengzhou, 450052, China. [email protected].
- 9Gene Hospital of Henan Province/Precision Medicine Center, the First Affiliated Hospital of Zhengzhou University, 1#, Jianshe East Road, Zhengzhou, 450052, China. [email protected].
Abstract
Background
While the association between gut microbiota and cholangiocarcinoma (CCA) has been explored, existing research has been limited to bacterial components. The alterations in non-bacterial members (fungi, archaea, and viruses) and their functional characteristics in CCA remain unclear. This study aimed to comprehensively characterize the multi-kingdom gut microbiota and functional profiles in CCA patients and develop a non-invasive diagnostic model.Methods
We performed metagenomic sequencing on 700 fecal samples collected from three distinct regions in China, comprising 289 CCA patients, 312 healthy controls, and 99 hepatocellular carcinoma (HCC) patients. Multi-kingdom microbial composition and functional profiles were analyzed. We integrated multiple machine learning algorithms to generate 117 distinct modeling schemes for constructing and screening the optimal CCA diagnostic model. The model was validated across three independent cohorts and tested for specificity against HCC. We also benchmarked the model against established diagnostic approaches by reviewing 15 CCA clinical practice guidelines/consensus statements and their cited evidence and by evaluating model detection in CA19-9-positive and CA19-9-negative patients.Results
Extensive alterations were identified in CCA patients across multi-kingdom and functional layers, including 198 archaeal, 154 bacterial, 78 fungal, and 120 viral species, as well as 278 genes, 99 pathways, and 151 carbohydrate-active enzymes (CAZymes). A panel of 21 multi-kingdom and functional markers demonstrated superior diagnostic accuracy with an average AUC of 91% across three validation cohorts, outperforming any single-kingdom model. The model exhibited high specificity in distinguishing CCA from HCC, achieving an AUC of 99.74% with a false positive rate of 11.11%. Benchmarking supported a complementary role as a noninvasive screening aid, the model showed pooled sensitivity and specificity of 96.2%, and 78.5%, respectively, and detected 97.6% of CA19-9-negative CCA cases.Conclusions
This study represents the first comprehensive characterization of multi-kingdom gut microbiome and functional markers in cholangiocarcinoma. Gut multi-kingdom and functional microbial signatures represent a promising noninvasive tool that may aid the screening and early identification of cholangiocarcinoma in high-risk populations, complementing existing diagnostic approaches.
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BibTeX
@article{rao2026multikingdom,
title = {{Multikingdom and functional gut microbiota markers for cholangiocarcinoma.}},
author = {Benchen Rao and Shanshuo Liu and Guangying Cui and Jianwen Jiang and Na Li and Ji Hu and Ranran Sun and Ang Li and Ruiqing Zhang and Haifeng Lu and Peihao Wen and Jianfeng Xue and Tuerganaili Aji and Haiyu Wang and Xiaolong Chen and Shusen Zheng and Zujiang Yu and Zhigang Ren},
journal = {Genome medicine},
year = {2026},
month = oct,
doi = {10.1186/s13073-026-01757-0},
url = {https://europepmc.org/article/MED/42958435},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Multikingdom and functional gut microbiota markers for cholangiocarcinoma.
AU - Benchen Rao
AU - Shanshuo Liu
AU - Guangying Cui
AU - Jianwen Jiang
AU - Na Li
AU - Ji Hu
AU - Ranran Sun
AU - Ang Li
AU - Ruiqing Zhang
AU - Haifeng Lu
AU - Peihao Wen
AU - Jianfeng Xue
AU - Tuerganaili Aji
AU - Haiyu Wang
AU - Xiaolong Chen
AU - Shusen Zheng
AU - Zujiang Yu
AU - Zhigang Ren
PY - 2026
DA - 2026/10/17
JO - Genome medicine
DO - 10.1186/s13073-026-01757-0
UR - https://europepmc.org/article/MED/42958435
AB - Background While the association between gut microbiota and cholangiocarcinoma (CCA) has been explored, existing research has been limited to bacterial components. The alterations in non-bacterial members (fungi, archaea, and viruses) and their functional characteristics in CCA remain unclear. This study aimed to comprehensively characterize the multi-kingdom gut microbiota and functional profiles in CCA patients and develop a non-invasive diagnostic model.Methods We performed metagenomic sequencing on 700 fecal samples collected from three distinct regions in China, comprising 289 CCA patients, 312 healthy controls, and 99 hepatocellular carcinoma (HCC) patients. Multi-kingdom microbial composition and functional profiles were analyzed. We integrated multiple machine learning algorithms to generate 117 distinct modeling schemes for constructing and screening the optimal CCA diagnostic model. The model was validated across three independent cohorts and tested for specificity against HCC. We also benchmarked the model against established diagnostic approaches by reviewing 15 CCA clinical practice guidelines/consensus statements and their cited evidence and by evaluating model detection in CA19-9-positive and CA19-9-negative patients.Results Extensive alterations were identified in CCA patients across multi-kingdom and functional layers, including 198 archaeal, 154 bacterial, 78 fungal, and 120 viral species, as well as 278 genes, 99 pathways, and 151 carbohydrate-active enzymes (CAZymes). A panel of 21 multi-kingdom and functional markers demonstrated superior diagnostic accuracy with an average AUC of 91% across three validation cohorts, outperforming any single-kingdom model. The model exhibited high specificity in distinguishing CCA from HCC, achieving an AUC of 99.74% with a false positive rate of 11.11%. Benchmarking supported a complementary role as a noninvasive screening aid, the model showed pooled sensitivity and specificity of 96.2%, and 78.5%, respectively, and detected 97.6% of CA19-9-negative CCA cases.Conclusions This study represents the first comprehensive characterization of multi-kingdom gut microbiome and functional markers in cholangiocarcinoma. Gut multi-kingdom and functional microbial signatures represent a promising noninvasive tool that may aid the screening and early identification of cholangiocarcinoma in high-risk populations, complementing existing diagnostic approaches.
SN - 1756-994X
ER -