{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,4]],"date-time":"2026-10-04T02:58:58Z","timestamp":1791082738703,"version":"4.1.0"},"reference-count":23,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T00:00:00Z","timestamp":1779062400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Genet."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>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\u2013hepatocyte\/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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Single-cell analysis revealed profound cellular heterogeneity within the HCC microenvironment, identifying six transcriptionally distinct macrophage subpopulations (M1\u2013M6) 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\u2013CD44\/ITGAV signaling axis as a dominant pathway mediating macrophage\u2013hepatocyte and macrophage\u2013fibroblast interactions. APOA2 demonstrated differential expression between normal and tumor tissues, with its downregulation strongly correlated with promoter methylation (Spearman \u03c1 = \u22120.31, P = 9.11 \u00d7 10\n                      <jats:sup>\u221210<\/jats:sup>\n                      ). Although APOA2 showed limited diagnostic performance (AUC = 0.552), APOA2-low tumors exhibited trends toward poorer clinical outcomes across multiple survival metrics. Integration of metabolomic and transcriptomic data revealed associations between APOA2 silencing, altered serum metabolite profiles, and enhanced macrophage activation, establishing a metabolic\u2013immune\u2013epigenetic cascade that promotes tumor fibrogenesis and progression. qRT-PCR validation in HCC cell lines confirmed differential expression of Genes encoding core components of the SPP1\u2013CD44\/ITGAV signaling axis that regulate macrophage\u2013tumor crosstalk and whose expression levels correlate with higher histological grade and increased metastatic risk in hepatocellular carcinoma in aggressive Huh7 cells (3.2-fold and 2.8-fold respectively, P &amp;lt; 0.001), while APOA2 was downregulated (0.35-fold, P &amp;lt; 0.001), corroborating bioinformatic predictions.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>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\u2013integrin signaling network. The identification of functionally distinct macrophage subpopulations and the metabolic\u2013immune\u2013epigenetic 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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fgene.2026.1819908","type":"journal-article","created":{"date-parts":[[2026,5,17]],"date-time":"2026-05-17T22:10:15Z","timestamp":1779055815000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Single-cell RNA sequencing unveils macrophage heterogeneity and cell-cell interactions in hepatocellular carcinoma progression"],"prefix":"10.3389","volume":"17","author":[{"given":"YiFei","family":"Tang","sequence":"first","affiliation":[{"name":"Department of Liver Diseases, ShuGuang Hospital Affiliated to Shanghai University of Chinese Traditional Medicine","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"JiaHui","family":"Li","sequence":"additional","affiliation":[{"name":"Department of TCM Gynecology, The International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"LingYing","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Liver Diseases, ShuGuang Hospital Affiliated to Shanghai University of Chinese Traditional Medicine","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,5,18]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"19591","DOI":"10.1038\/s41598-024-69998-w","article-title":"Discovering the lipid metabolism-related hub genes of HCC-treated samples with PPARalpha agonist through weighted correlation network analysis","volume":"14","author":"AmeliMojarad","year":"2024","journal-title":"Sci. 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