ArticleFrontiers in oncology2025
SPP1+ tumor-associated macrophages define a high-risk subgroup and inform personalized therapy in hepatocellular carcinoma.
Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Spatial multi omic profiling maps hypoxia-driven pro-fibrotic SPP1Experimental hematology & oncology · 2026Article
- Hepatocellular carcinoma metastasis-immune microenvironment crosstalk: emerging mechanisms and immunotherapy.Cellular & molecular biology letters · 2026Review
- SpaPheno: linking spatial transcriptomics to clinical phenotypes with interpretable machine learning.Genome medicine · 2026Article
- Molecular mechanisms of tumor-associated macrophages in hepatocellular carcinoma development and therapy.World journal of gastroenterology · 2026Review
- SPP1+ Macrophages and the Orchestration of Spatially Organized Immunosuppression in Cancer.Biomedicines · 2026Review
- IntratumoralDiagnostics (Basel, Switzerland) · 2025Article
- Review
- Adrenomedullin orchestrates treatment resistance in hepatocellular carcinoma via immune microenvironment remodeling.Frontiers in genetics · 2025Article
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Authors and funding
8 authors.
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Abstract
Introduction: Recently, contrary to attacking cancer cells, the tumor microenvironment (TME) with genomic stability and vulnerable nature has emerged as promising therapeutic targets in hepatocellular carcinoma (HCC). Within TME ecosystem, tumor-associated macrophages (TAMs) play a pivotal role in tumor evasion and progression of HCC. However, their clinical and therapeutic implications remain unexplored. Methods: Utilizing a large-scale sc-RNA seq dataset, a landscape of HCC cellular ecosystem was depicted. Based on previous literature, an effectively differential TAMs subset classification was identified. Gene variations was extracted through trajectory analysis and then unsupervised clustering was conducted within RNA-seq data. Subsequently, survival analysis, specific pathway enrichment as well as hub regulatory network analysis were performed. Additionally, the immune cell infiltration and genomic variations were evaluated between clusters. Drug sensitivity and underlying therapeutic molecular were also explored. Through multiple immunofluorescence, our findings were verified. Results: Herein, integrating single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data, we established a novel TAM classification system based on mutually exclusive Conclusion: This study redefines the heterogeneity of TAMs beyond the M1/M2 paradigm, linking the TAMs trajectory genes to HCC patient stratification.
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