ArticleHepatology (Baltimore, Md.)2018
A Large-scale, multicenter serum metabolite biomarker identification study for the early detection of hepatocellular carcinoma.
Article in Hepatology (Baltimore, Md.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 219 papers, 5 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
219 citing papers in PubMed, 5 syntheses or guidelines pooled it, 369 citations in OpenAlex.
- A bibliometric and text-mining analysis of lipidomics and metabolomics in human disease.Frontiers in physiology · 2026Pooled it
- Dysregulation of serum bile acids in liver cancer: a systematic review and meta-analysis.Metabolomics : Official journal of the Metabolomic Society · 2025Pooled it
- Abdominal ultrasound and alpha-foetoprotein for the diagnosis of hepatocellular carcinoma in adults with chronic liver disease.The Cochrane database of systematic reviews · 2021Pooled it
- Diagnostic Accuracy of Serum/Plasma Circular RNAs and the Combination of Circular RNAs and α-Fetoprotein for Detecting Hepatocellular Carcinoma: A Meta-Analysis.Frontiers in genetics · 2021Pooled it
- Evaluation of the Combined Application of AFP, AFP-L3%, and DCP for Hepatocellular Carcinoma Diagnosis: A Meta-analysis.BioMed research international · 2020Pooled it
- Single-cell immune signature for detecting early-stage HCC and early assessing anti-PD-1 immunotherapy efficacy.Journal for immunotherapy of cancer · 2022Trial
- Metabolic Signatures for Liver Cancer Diagnosis and Mechanistic Insights: A Large-Scale, Multicenter Study.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- MS-FGNet: An Attention-Guided Deep Learning Framework for Fine-Grained Pathological Subtype Prediction from DIA Proteomics Imaging.Journal of imaging informatics in medicine · 2026Article
- Development and validation of a multiplexed targeted HILIC-HRMS assay for quantitative analysis of hepatocellular carcinoma circulating biomarkers.Analytical and bioanalytical chemistry · 2026Article
- Article
- Integrated serum proteomics and metabolomics reveal an INR-associated multi-omics signature in hepatocellular carcinoma.Clinical proteomics · 2026Article
- Gut microbiome and bile acid metabolism in liver disease: Mechanisms, clinical implications, and therapeutic opportunities.Pharmacological reviews · 2026Review
- Systematic review of metabolomic profiles linked to liver cancer.Journal of liver cancer · 2026Article
- Insulin resistance: mechanisms and therapeutic interventions.Molecular biomedicine · 2026Review
- Non-invasive liquid biopsy based on metabolomic profiling improves diagnosis and early warning of severe acute pancreatitis.NPJ digital medicine · 2026Article
- Development and Validation of Predictive Machine Learning Models for Postoperative Recurrence and Microvascular Invasion in Hepatocellular Carcinoma Using Nuclear Magnetic Resonance Metabolomics.Journal of hepatocellular carcinoma · 2026Article
- Review
- Metabolic reprogramming in sepsis-associated encephalopathy: emerging mechanisms, candidate biomarkers, and future therapeutic directions.Frontiers in medicine · 2026Review
- Decoding amino acid metabolism in hepatocellular carcinoma: critical nodes and novel therapeutic strategy.Frontiers in oncology · 2026Review
- CYP8B1 inhibits hepatocellular carcinoma progression by repressing PAK4 transcription through inhibition of nuclear translocation of u-STAT1.Cell death & disease · 2025Article
159 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
20 authors at 7 institutions in 1 country.
Funding
Abstract
Hepatocellular carcinoma (HCC) is the third most lethal cancer worldwide. The lack of effective biomarkers for the early detection of HCC results in unsatisfactory curative treatments. Here, metabolite biomarkers were identified and validated for HCC diagnosis. A total of 1,448 subjects, including healthy controls and patients with chronic hepatitis B virus infection, liver cirrhosis, and HCC, were recruited from multiple centers in China. Liquid chromatography-mass spectrometry-based metabolomics methods were used to characterize the subjects' serum metabolic profiles and to screen and validate the HCC biomarkers. A serum metabolite biomarker panel including phenylalanyl-tryptophan and glycocholate was defined. This panel had a higher diagnostic performance than did α-fetoprotein (AFP) in differentiating HCC from a high-risk population of cirrhosis, such as an area under the receiver-operating characteristic curve of 0.930, 0.892, and 0.807 for the panel versus 0.657, 0.725, and 0.650 for AFP in the discovery set, test set, and cohort 1 of the validation set, respectively. In the nested case-control study, this panel had high sensitivity (range 80.0%-70.3%) to detect preclinical HCC, and its combination with AFP provided better risk prediction of preclinical HCC before clinical diagnosis. Besides, this panel showed a larger area under the receiver-operating characteristic curve than did AFP (0.866 versus 0.682) to distinguish small HCC, and 80.6% of the AFP false-negative patients with HCC were correctly diagnosed using this panel in the test set, which was corroborated by the validation set. The specificity and biological relevance of the identified biomarkers were further evaluated using sera from another two cancers and HCC tissue specimens, respectively. Conclusion: The discovered and validated serum metabolite biomarker panel exhibits good diagnostic performance for the early detection of HCC from at-risk populations. (Hepatology 2018;67:662-675).
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.