Evidence map›Paper›PMID 28454235›Full record

ArticleOncology letters2017

Metabolic profiling of hepatitis B virus-related hepatocellular carcinoma with diverse differentiation grades.

Lei Zhang, Ya Huang, Mingjian Lian, Zhijuan Fan, Yaqiong Tian, Yufan Wang, Hua Kang, Shuang Liu, Shuye Liu, Tong Li and 1 more

Abstract read
In one paragraph

Article in Oncology letters, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Dysregulation of serum bile acids in liver cancer: a systematic review and meta-analysis.Metabolomics : Official journal of the Metabolomic Society · 2025
    Pooled it
  2. Review
  3. Article
  4. Metabolomics Analysis of Viral Therapeutics.Methods in molecular biology (Clifton, N.J.) · 2021
    Article
  5. Article
  6. Article
  7. Observational
  8. A Study on Tissue-Specific Metabolite Variations inMolecules (Basel, Switzerland) · 2019
    Article
  9. Article
  10. Article
  11. Article
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

11 authors.

Lei ZhangTianjin Key Laboratory of Artificial Cell, Artificial Cell Engineering Technology Research Center of Public Health Ministry, Tianjin Third Central Hospital, Tianjin 300170, P.R. China.
Ya HuangClinical Laboratory Department, Chongqing City First People's Hospital of Wanzhou, Chongqing 404040, P.R. China.
Mingjian LianClinical Laboratory Department, Third Central Clinical College, Tianjin Medical University, Tianjin 300070, P.R. China.
Zhijuan FanTianjin Key Laboratory of Artificial Cell, Clinical Laboratory Department, Tianjin Third Central Hospital, Tianjin 300170, P.R. China.
Yaqiong TianTianjin Key Laboratory of Artificial Cell, Clinical Laboratory Department, Tianjin Third Central Hospital, Tianjin 300170, P.R. China.
Yufan WangTianjin Key Laboratory of Artificial Cell, Clinical Laboratory Department, Tianjin Third Central Hospital, Tianjin 300170, P.R. China.
Hua KangTianjin Key Laboratory of Artificial Cell, Clinical Laboratory Department, Tianjin Third Central Hospital, Tianjin 300170, P.R. China.
Shuang LiuClinical Laboratory Department, Third Central Clinical College, Tianjin Medical University, Tianjin 300070, P.R. China.
Shuye LiuTianjin Key Laboratory of Artificial Cell, Clinical Laboratory Department, Tianjin Third Central Hospital, Tianjin 300170, P.R. China.
Tong LiTianjin Key Laboratory of Artificial Cell, Clinical Laboratory Department, Tianjin Third Central Hospital, Tianjin 300170, P.R. China.
Zhongqiang ShanChemical Engineering Institute, Tianjin University, Tianjin 300072, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The most effective diagnostic tool for the majority of hepatocellular carcinoma (HCC) patients is determining the differentiation grade of their tumors. However liver biopsies, which are currently the most effective way of determining tumor differentiation grade, have several limitations. The present study was designed to select serum characteristic metabolites that correlate with the differentiation grades of hepatitis B virus (HBV)-related HCC, and so could be used in the clinic as a non-invasive method of differentiating patients with different grades of HCC. A total of 58 patients with HBV-related HCC were included in the present study, and divided into three groups according to their tumor differentiation grade. A further 20 patients with HBV-related liver cirrhosis and 19 healthy volunteers were enrolled. Ultra-performance liquid chromatography-mass spectrometry was used to analyze endogenous metabolites. Multivariate statistical analysis was used to examine the data using MZmine 2.0 software. The 14 metabolites that were highly correlated with specific differentiation grades of HCC were then selected for additional study. Receiver operator characteristic curve analysis was used to evaluate their clinical value. In total, 5 metabolites were finally identified, including lysophosphatidylcholine (16:0), oleamide, monoglyceride (0:0/15:0/0:0), lysophosphatidylcholine (18:0) and lysophosphatidylcholine [22:5(7Z,10Z,13Z,16Z,19Z)]. All these metabolites exhibited an excellent ability to distinguish different types of HCC with various differentiation grades and the area under the curve of these metabolites was up to 0.942, showing promising clinical value.

Indexed as

characteristic metaboliteshepatocellular carcinoma metabolomicsultra performance liquid chromatography-mass spectrometry

Identifiers

PMID28454235
PMCPMC5403281

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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.