Evidence map›Paper›PMID 40657162›Full record

ArticlePrecision clinical medicine2025

Decoding hepatobiliary-specific immune gene patterns in gastrointestinal cancers via gene ontology fingerprints, multi-omics, and experimental integration.

Honglian Huang, Yueping Zhan, Hui Zong, Chenjun Huang, Fan Yang, Ziyi Wei, Xin Qin, M James C Crabbe, Ying Wang, Xiaoyan Zhang

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PubMed Full text at PMC Publisher
In one paragraph

Article in Precision clinical medicine, 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

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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

10 authors.

Honglian HuangDepartment of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.ORCID https://orcid.org/0009-0003-2739-5348
Yueping ZhanDepartment of Clinical Laboratory Medicine Center, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China.
Hui ZongDepartment of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
Chenjun HuangDepartment of Clinical Laboratory Medicine Center, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China.
Fan YangState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310058, China.
Ziyi WeiDepartment of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
Xin QinDepartment of Clinical Laboratory Medicine Center, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China.
M James C CrabbeWolfson College, Oxford University, Oxford OX2 6UD, United Kingdom.
Ying WangDepartment of Clinical Laboratory Medicine Center, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China.
Xiaoyan ZhangDepartment of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.ORCID https://orcid.org/0000-0003-1562-0045

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Gastrointestinal (GI) cancers are characterized by high malignancy and poor prognosis. Tumors in different locations exhibit both commonalities and differences. Although immunotherapy has made progress in some GI cancers, the specific immune-related patterns in hepatobiliary tumors have not yet been fully elucidated. Methods: Using our developed explainable gene ontology fingerprint (XGOF) method, a GI cancer GOF was established. By integrating omics data from 20 hepatocellular carcinoma (HCC) and 15 intrahepatic cholangiocarcinoma (ICC) tissues in our clinic with public databases, immune-related patterns specifically expressed in hepatobiliary tumors were identified via RNA, protein, methylation, tumor microenvironment (TME) analysis, and experimental verification. Results: XGOF showed that GI cancers are related to diverse immune functions, especially macrophage migration. Compared to others, hepatobiliary tumors exhibit distinct patterns of gene expression, mutation, and methylation. Seven genes (APOA1, LBP, FGA, C9, APCS, ARG1, and MBL2) were identified as immune-related genes specifically decreased in hepatobiliary cancer. The impact of APOA1 on TME, prognosis, and genomic landscape in HCC was explored in prior research. In this work, the experiment confirmed the down-regulation of six genes in cancerous tissues. Moreover, LBP promoter methylation was elevated in cholangiocarcinoma. Single-cell analysis revealed downregulated immune genes in hepatocytes of HCC and cholangiocytes of ICC, enriched in humoral immunity and complement pathways. Additionally, the macrophage migration inhibitory factor (MIF) pathway was identified as a key signal in interactions between ICC tumor cells and microenvironmental cells. Conclusion: This study identified immune-related gene patterns in hepatobiliary cancer, contributing to the discovery of novel immunotherapy targets and tumor biomarkers for future research.

Indexed as

gastrointestinal cancerhepatobiliary tumorimmune-related genemultidimensional analysis

Identifiers

PMID40657162
PMCPMC12256135

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