Evidence map›Paper›PMID 39243943›Full record

SynthesisJournal of advanced research2025

Metabolic phenotyping combined with transcriptomics metadata fortifies the diagnosis of early-stage Hepatocellular carcinoma.

Sun Jo Kim, Cheol Woon Jung, Nguyen Hoang Anh, Young Cheol Yoon, Nguyen Phuoc Long, Soon-Sun Hong, Eun Ju Cho, Sung Won Kwon

Abstract readMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Journal of advanced research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Sun Jo KimResearch Institute of Pharmaceutical Sciences, Seoul National University, Seoul 08826, Republic of Korea; College of Pharmacy, Chonnam National University, Gwangju 61186, Republic of Korea.
Cheol Woon JungCollege of Pharmacy, Seoul National University, Seoul 08826, Republic of Korea.
Nguyen Hoang AnhResearch Institute of Pharmaceutical Sciences, Seoul National University, Seoul 08826, Republic of Korea; College of Pharmacy, Seoul National University, Seoul 08826, Republic of Korea.
Young Cheol YoonCollege of Pharmacy, Seoul National University, Seoul 08826, Republic of Korea.
Nguyen Phuoc LongDepartment of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan 47392, Republic of Korea.
Soon-Sun HongDepartment of Biomedical Science, College of Medicine, and Program in Biomedical Sciences and Engineering, Inha University, Incheon 22332, Republic of Korea.
Eun Ju ChoDepartment of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul 03080, Republic of Korea.
Sung Won KwonResearch Institute of Pharmaceutical Sciences, Seoul National University, Seoul 08826, Republic of Korea; College of Pharmacy, Seoul National University, Seoul 08826, Republic of Korea; Plant Genomics and Breeding Institute, Seoul National University, Seoul 08826, Republic of Korea. Electronic address: swkwon@snu.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe low sensitivity of alpha-fetoprotein (AFP) renders it unsuitable as a stand-alone marker for early hepatocellular carcinoma (eHCC) surveillance. Therefore, additional blood-based biomarkers with enhanced sensitivities are required.

objectivesIn light of the metabolic changes that are distinctive to eHCC development, the current study presents a panel of serum metabolites that may serve as noninvasive diagnostic indicators for patients with eHCC.

methodsSerum samples obtained from normal control (NC), cirrhosis, and eHCC patients were analyzed by four different metabolomic platforms. A meta-analysis of very early-stage HCC transcriptomic datasets retrieved from public sources supports the integrated interpretation with metabolic changes.

resultsA total of 94 metabolites were significantly correlated with a progressive disease status. Integrated analysis of the significant metabolites and differentially expressed genes from meta-analysis emphasized metabolic pathways including bile acid biosynthesis, phenylalanine and tyrosine metabolism, and butanoate metabolism. The 11 metabolites associated with these pathways were compiled into a metabolite panel for use as diagnostic signatures. With an accuracy of 81.8%, compared with 45.4% for a model trained solely on AFP, the model enhanced its ability to differentiate between the three groups by incorporating a metabolite panel and AFP. Upon examining the trained models using receiver operating characteristic curves, the AFP and metabolite panel combined model exhibited greater area under the curve values in comparisons between NC and eHCC (1.000 versus 0.810) and cirrhosis and eHCC (0.926 versus 0.556). The result was consistent in an independent validation cohort.

conclusionThis study emphasizes the role of circulating metabolite markers in the diagnosis of eHCC.

Indexed as

Biomarkers, TumorCarcinoma, HepatocellularLiver NeoplasmsTranscriptomealpha-FetoproteinsEarly Detection of CancerFemaleGene Expression ProfilingHumansMaleMetabolomicsMetadataMiddle AgedPhenotypealpha-FetoproteinsBiomarkers, TumorCarcinoma, HepatocellularEarly diagnosisGene expression profilingMachine learningMetabolomics

Identifiers

PMID39243943
PMCPMC12302345

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.