Evidence map›Paper›PMID 40730701›Full record

ArticleDiscover oncology2025

Heterogeneity of the liver cancer tumor microenvironment: mitochondrial metabolism and causal inference through Mendelian randomization.

Xiaping Liu, Zhang Jing, Jian Chen, Linhong Su, Jun Lin, Xiaoqu Zhu, Xiaodan Ye

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Xiaping Liu *Department of Infectious Liver Disease, Wenzhou TCM Hospital of Zhejiang Chinese Medical University, Wenzhou, 325000, China.
Zhang Jing *Department of Ultrasound, The Second Affiliated Hospital of Chengdu Medical College, Nuclear Industry 416 Hospital, Chengdu, 610000, China.
Jian ChenDepartment of Infectious Liver Disease, Wenzhou TCM Hospital of Zhejiang Chinese Medical University, Wenzhou, 325000, China.
Linhong SuDepartment of Infectious Liver Disease, Wenzhou TCM Hospital of Zhejiang Chinese Medical University, Wenzhou, 325000, China.
Jun LinDepartment of Infectious Liver Disease, Wenzhou TCM Hospital of Zhejiang Chinese Medical University, Wenzhou, 325000, China.
Xiaoqu ZhuDepartment of Infectious Liver Disease, Wenzhou TCM Hospital of Zhejiang Chinese Medical University, Wenzhou, 325000, China.
Xiaodan YeDepartment of Infectious Liver Disease, Wenzhou TCM Hospital of Zhejiang Chinese Medical University, Wenzhou, 325000, China. xd13616665186@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study presents a comprehensive investigation into the molecular mechanisms of hepatocellular carcinoma (HCC) through an innovative application of Mendelian randomization (MR) analysis, integrated with immune cell profiling and metabolomic assessment.

methodsUtilizing two-sample Mendelian randomization (TSMR) with data from large-scale GWAS studies, including immune cell profiles from the UK Biobank (n = 1629) and HCC cases from a multi-ethnic meta-analysis (775 cases, 1332 controls), we identified significant causal associations between specific immune cell populations, serum metabolites, and HCC risk. This study employed a multi-omics approach, including Principal Component Analysis (PCA), Gene Set Enrichment Analysis (GSEA), to conduct a comprehensive analysis of the liver cancer TME.

resultsOur analysis revealed three immune cell populations significantly associated with HCC development: CD127-expressing CD28 + CDACDB-T cells (OR = 1.31), and unswitched memory B cells measured by both percentage (OR = 1.57) and absolute count (OR = 1.49). We found an increased dispersion of tumor cells in PCA, reflecting adaptive changes due to complex gene regulatory networks. The TYROBP gene was specifically expressed in myeloid cells and enriched in multiple biological pathways. Cell communication analysis revealed significant interactions between T cells and tumor cells.

conclusionThis study provides a comprehensive view of the heterogeneity of the liver cancer TME and reveals the potential roles of key genes and cell types in the development of liver cancer. These findings offer new insights into the molecular mechanisms of liver cancer and may aid in the identification of new therapeutic targets and biomarkers.

Indexed as

Cell communicationGene expressionImmune cellsLiver cancerMulti-omics analysisTumor microenvironment

Identifiers

PMID40730701
PMCPMC12307838

What Socratic 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 Socratic graph.