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通过基因本体指纹、多组学和实验整合解码胃肠道癌症中的肝胆特异性免疫基因模式。

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

作者信息

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

机构信息

Department of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.

Department of Clinical Laboratory Medicine Center, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China.

出版信息

Precis Clin Med. 2025 Jun 24;8(3):pbaf014. doi: 10.1093/pcmedi/pbaf014. eCollection 2025 Sep.

DOI:10.1093/pcmedi/pbaf014
PMID:40657162
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12256135/
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.

摘要

背景

胃肠道(GI)癌症具有高恶性和预后差的特点。不同部位的肿瘤既有共性也有差异。尽管免疫疗法在某些胃肠道癌症中取得了进展,但肝胆肿瘤中特定的免疫相关模式尚未完全阐明。

方法

使用我们开发的可解释基因本体指纹(XGOF)方法,建立了胃肠道癌症基因本体指纹。通过将我们诊所中20例肝细胞癌(HCC)和15例肝内胆管癌(ICC)组织的组学数据与公共数据库相结合,通过RNA、蛋白质、甲基化、肿瘤微环境(TME)分析和实验验证,确定了在肝胆肿瘤中特异性表达的免疫相关模式。

结果

XGOF显示胃肠道癌症与多种免疫功能相关,尤其是巨噬细胞迁移。与其他癌症相比,肝胆肿瘤表现出独特的基因表达、突变和甲基化模式。七个基因(载脂蛋白A1、脂多糖结合蛋白、纤维蛋白原α链、补体C9、补体成分S、精氨酸酶1和甘露糖结合凝集素2)被确定为在肝胆癌中特异性降低的免疫相关基因。先前的研究探讨了载脂蛋白A1对肝癌TME、预后和基因组格局的影响。在这项工作中,实验证实了癌组织中六个基因的下调。此外,胆管癌中脂多糖结合蛋白启动子甲基化升高。单细胞分析显示肝癌肝细胞和肝内胆管癌胆管细胞中的免疫基因下调,富集于体液免疫和补体途径。此外,巨噬细胞迁移抑制因子(MIF)途径被确定为肝内胆管癌肿瘤细胞与微环境细胞相互作用中的关键信号。

结论

本研究确定了肝胆癌中的免疫相关基因模式,有助于发现新的免疫治疗靶点和肿瘤生物标志物,以供未来研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcc1/12256135/15b33b4d25a1/pbaf014fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcc1/12256135/38068595318b/pbaf014fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcc1/12256135/13309eda73a6/pbaf014fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcc1/12256135/5d72456c6981/pbaf014fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcc1/12256135/b393edcb0df9/pbaf014fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcc1/12256135/ff617ba95d5a/pbaf014fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcc1/12256135/15b33b4d25a1/pbaf014fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcc1/12256135/38068595318b/pbaf014fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcc1/12256135/13309eda73a6/pbaf014fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcc1/12256135/5d72456c6981/pbaf014fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcc1/12256135/b393edcb0df9/pbaf014fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcc1/12256135/ff617ba95d5a/pbaf014fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcc1/12256135/15b33b4d25a1/pbaf014fig6.jpg

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