Work

Machine learning-based tumor associated macrophages polarity signature predicts prognosis and treatment response in hepatocellular carcinoma

Year: 2025

Type: article

Abstract: Background: Tumor-associated macrophages (TAMs) shape the tumor microenvironment and drive hepatocellular carcinoma (HCC) progression. However, the prognostic significance of TAM polarity-related genes, particularly based on the CXCL9:SPP1 signature, remains unclear. Methods: We identified 372 TAM polarity-related genes in the TCGA-LIHC dataset. Prognostic candidates were selected using univariate Cox regression, bootstrap resampling, and the Boruta algorithm. Seven machine learning models were compared, and XGBoost was selected to construct a TAM polarity-related signature (TPS) consisting of 17 genes. TPS was validated in two external cohorts. Associations with clinical features, biological pathways, immune status, and drug sensitivity were explored. scRNA-seq and qRT-PCR were performed to investigate cellular expression and functional relevance. Results: TPS markedly different patients into high- and low-risk groups with significantly different survival outcomes (TCGA 1-, 3-, 5-year AUCs: 0.91, 0.89, 0.88). High-risk patients showed enrichment in glycan metabolism, DNA repair, and oncogenic pathways, whereas low-risk patients displayed elevated lipid and amino acid metabolism. Immune profiling revealed greater infiltration of immunosuppressive cells and higher expression of immune checkpoints in high-risk patients. Drug sensitivity analysis identified potential therapeutic targets and candidate compounds, including CDK1, PLK1, and statins. scRNA-seq analysis highlighted disrupted macrophage-immune interactions and identified SPP1 as a key signaling mediator. Silencing of TTC1 and G6PD suppressed HCC cell proliferation. Conclusion: We developed and validated a robust TAM polarity-related signature that effectively stratifies HCC patients by prognosis. TPS provides insights into tumor immunity, metabolism, and drug response, and may serve as a valuable tool for precision medicine in HCC.

Source: Frontiers in Immunology

DOI: 10.3389/fimmu.2025.1663519

Authors: Fangzhou Wang, Quan Zhang, Shichun Lu, Yamin Zheng

Institutions: Capital Medical University, Xuan Wu Hospital of the Capital Medical University, Chinese PLA General Hospital, Chinese People's Liberation Army

Language: English

Topic: Immune cells in cancer

Subfield: Immunology

Field: Immunology and Microbiology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,801