Evidence map›Paper›PMID 42227003›Full record

ArticleFrontiers in genetics2026

Single-cell RNA sequencing unveils macrophage heterogeneity and cell-cell interactions in hepatocellular carcinoma progression.

YiFei Tang, JiaHui Li, LingYing Huang

Abstract read
In one paragraph

Article in Frontiers in genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

YiFei TangDepartment of Liver Diseases, ShuGuang Hospital Affiliated to Shanghai University of Chinese Traditional Medicine, Shanghai, China.
JiaHui LiDepartment of TCM Gynecology, The International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
LingYing HuangDepartment of Liver Diseases, ShuGuang Hospital Affiliated to Shanghai University of Chinese Traditional Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hepatocellular carcinoma (HCC) represents a major global health burden, characterized by complex metabolic reprogramming and immunological dysregulation. This study aimed to elucidate the molecular mechanisms underlying HCC progression using integrative multi-omics analyses, with a specific focus on macrophage heterogeneity and intercellular communication networks in the tumor microenvironment. Methods: We performed comprehensive bioinformatic analyses integrating gene expression profiling, DNA methylation data, and single-cell RNA sequencing (scRNA-seq) datasets from publicly available databases. Single-cell transcriptomic data (GSE149614) were processed using Seurat for quality control, dimensionality reduction, and cell type annotation. Macrophage subpopulation diversity was assessed through Weighted Gene Co-expression Network Analysis (WGCNA) and differential expression analysis. Intercellular communication networks were reconstructed using CellPhoneDB and CellChat to identify Signaling axes that act as primary mediators of macrophage-hepatocyte/fibroblast crosstalk in HCC. Functional enrichment analyses were conducted via Gene Ontology and KEGG pathway analyses. The diagnostic and prognostic potential of genes whose expression or methylation status predicts HCC stage, metastasis risk, and patient survival was evaluated through Receiver Operating Characteristic curve analysis and survival modeling. Expression patterns of genes whose dysregulation directly disrupts immunometabolic crosstalk between macrophages and tumor cells, whose dysregulation increases the risk of hepatocellular carcinoma progression by promoting an immunosuppressive microenvironment and enhancing tumor cell proliferation and invasion were experimentally validated using quantitative real-time PCR (qRT-PCR) in two hepatocellular carcinoma cell lines (HepG2 and Huh7) obtained from American Type Culture Collection. Results: Single-cell analysis revealed profound cellular heterogeneity within the HCC microenvironment, identifying six transcriptionally distinct macrophage subpopulations (M1-M6) with unique immunometabolic signatures. M2-like subsets were enriched in extracellular matrix organization and integrin-mediated signaling pathways, supporting their pro-fibrotic and immunosuppressive roles. Intercellular communication network analysis identified the SPP1-CD44/ITGAV signaling axis as a dominant pathway mediating macrophage-hepatocyte and macrophage-fibroblast interactions. APOA2 demonstrated differential expression between normal and tumor tissues, with its downregulation strongly correlated with promoter methylation (Spearman ρ = -0.31, P = 9.11 × 10 Conclusion: This study unveils Macrophages that orchestrate the majority of intercellular signaling interactions in the HCC microenvironment orchestrating the immunometabolic landscape of HCC through the SPP1-integrin signaling network. The identification of functionally distinct macrophage subpopulations and the metabolic-immune-epigenetic axis involving APOA2 provides novel mechanistic insights into HCC pathogenesis and identifies genes and signaling axes whose pharmacological inhibition can reverse immunosuppression and block HCC progression for precision intervention strategies.

Indexed as

APOA2epigenetic regulationhepatocellular carcinomaintercellular communicationmacrophage heterogeneitysingle-cell RNA sequencingtumor microenvironment

Identifiers

PMID42227003
PMCPMC13222663

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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.