ArticleBritish journal of cancer2024
Urinary microbiome-based metagenomic signature for the noninvasive diagnosis of hepatocellular carcinoma.
Article in British journal of cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 9 citations in OpenAlex.
- The Current Landscape of Microbial Biomarkers in Gastrointestinal Disease.Gastroenterology clinics of North America · 2026Review
- Understanding crosstalk between the gut and liver microbiome: pathogenesis to therapeutic approaches in liver cancer.Cancer cell international · 2025Review
- The Gut Microbiome in Hepatocellular Carcinoma: Proliferation, Inhibition, Diagnosis, and Immunotherapy.Journal of microbiology and biotechnology · 2025Review
- Machine learning models for pancreatic cancer diagnosis based on microbiome markers from serum extracellular vesicles.Scientific reports · 2025Article
- Gut Microbiota and the Gut-liver Axis in Hepatocellular Carcinoma: A Comprehensive Review of Pathogenesis and Therapeutic Strategies.Anti-cancer agents in medicinal chemistry · 2025Review
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Authors and funding
10 authors at 1 institution in 2 countries.
Funding
Abstract
backgroundGut microbial dysbiosis is implicated in chronic liver disease and hepatocellular carcinoma (HCC), but the role of microbiomes from various body sites remains unexplored. We assessed disease-specific alterations in the urinary microbiome in HCC patients, investigating their potential as diagnostic biomarkers.
methodsWe performed cross-sectional analyses of urine samples from 471 HCC patients and 397 healthy controls and validated the results in an independent cohort of 164 HCC patients and 164 healthy controls. Urinary microbiomes were analyzed by 16S rRNA gene sequencing. A microbial marker-based model distinguishing HCC from controls was built based on logistic regression, and its performance was tested.
resultsMicrobial diversity was significantly reduced in the HCC patients compared with the controls. There were significant differences in the abundances of various bacteria correlated with HCC, thus defining a urinary microbiome-derived signature of HCC. We developed nine HCC-associated genera-based models with robust diagnostic accuracy (area under the curve [AUC], 0.89; balanced accuracy, 81.2%). In the validation, this model detected HCC with an AUC of 0.94 and an accuracy of 88.4%.
conclusionsThe urinary microbiome might be a potential biomarker for the detection of HCC. Further clinical testing and validation of these results are needed in prospective studies.
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