Evidence map›Paper›PMID 37887372›Full record

ArticleMetabolites2023

Biomarker Discovery for Hepatocellular Carcinoma in Patients with Liver Cirrhosis Using Untargeted Metabolomics and Lipidomics Studies.

Md Mamunur Rashid, Rency S Varghese, Yuansong Ding, Habtom W Ressom

Abstract read
In one paragraph

Article in Metabolites, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Evaluation of metabolite biomarker candidates in detecting HCC in patients with liver cirrhosis.Metabolomics : Official journal of the Metabolomic Society · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Integrative Analysis of Multi-Omics Data for Biomarker Discovery.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
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  17. 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

4 authors.

Md Mamunur RashidLombardi Comprehensive Cancer Center, Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington, DC 20057, USA.
Rency S VargheseLombardi Comprehensive Cancer Center, Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington, DC 20057, USA.ORCID 0000-0002-4236-7316
Yuansong DingLombardi Comprehensive Cancer Center, Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington, DC 20057, USA.
Habtom W RessomLombardi Comprehensive Cancer Center, Department of Oncology, Georgetown University Medical Center, Georgetown University, Washington, DC 20057, USA.ORCID 0000-0001-9296-2132

Funding

Systems Metabolomics for Biomarker DiscoveryR35GM141944 · NIGMS · GEORGETOWN UNIVERSITY · PI RESSOM, HABTOM W · 2021 to 2025
$2.4M
NIGMS NIH HHS R35 GM141944
6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is the third leading cause of mortality globally. Patients with HCC have a poor prognosis due to the fact that the emergence of symptoms typically occurs at a late stage of the disease. In addition, conventional biomarkers perform suboptimally when identifying HCC in its early stages, heightening the need for the identification of new and more effective biomarkers. Using metabolomics and lipidomics approaches, this study aims to identify serum biomarkers for identification of HCC in patients with liver cirrhosis (LC). Serum samples from 20 HCC cases and 20 patients with LC were analyzed using ultra-high-performance liquid chromatography-Q Exactive mass spectrometry (UHPLC-Q-Exactive-MS). Metabolites and lipids that are significantly altered between HCC cases and patients with LC were identified. These include organic acids, amino acids, TCA cycle intermediates, fatty acids, bile acids, glycerophospholipids, sphingolipids, and glycerolipids. The most significant variability was observed in the concentrations of bile acids, fatty acids, and glycerophospholipids. In the context of HCC cases, there was a notable increase in the levels of phosphatidylethanolamine and triglycerides, but the levels of fatty acids and phosphatidylcholine exhibited a substantial decrease. In addition, it was observed that all of the identified metabolites exhibited a superior area under the receiver operating characteristic (ROC) curve in comparison to alpha-fetoprotein (AFP). The pathway analysis of these metabolites revealed fatty acid, lipid, and energy metabolism as the most impacted pathways. Putative biomarkers identified in this study will be validated in future studies via targeted quantification.

Indexed as

biomarkersLC-MS/MSlipidomic profilingliver cancermetabolomic profiling

Identifiers

PMID37887372
PMCPMC10608999

What Socratic holds

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LicenceCC BY
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 Socratic graph.