SPP1 ⁺ Macrophage‐Associated Prognostic Signature in Hepatocellular Carcinoma via Integrated Single‐Cell and Bulk Transcriptomic Analysis

<b>Background:</b> Hepatocellular carcinoma (HCC) is a major cause of cancer mortality, with limited treatment options due to its high heterogeneity. SPP1⁺ tumor-associated macrophages are emerging as key regulators of the tumor immune microenvironment and disease progression. <b>Methods:</b> We integrated scRNA-seq data from the GEO database with bulk transcriptomic data from TCGA and ICGC. Immune cell subsets were identified through clustering and ligand-receptor interaction analyses. Prognostic genes associated with SPP1⁺ macrophages were screened using univariate Cox and Lasso regression. A risk model was built and validated using survival analysis and ROC curves. A multialgorithm AI framework was applied to enhance model performance. <b>Results:</b> Twelve immune cell types were identified, with SPP1⁺ macrophages showing strong interactions with tumor and immune cells. A seven-gene signature (SNX5, YBX1, GNPD1, RAB32, TPM3, ATP6V0B, and RAB7A) was constructed, effectively stratifying patients by survival risk in both TCGA and ICGC cohorts. The model showed strong predictive power with high AUC values and a significant correlation between gene expression and risk scores. <b>Conclusion:</b> SPP1⁺ macrophages play a crucial role in HCC immune modulation and progression. The gene signature developed provides a reliable tool for prognosis and may inform personalized treatment. This SPP1⁺ macro-associated signature offers a novel and robust biomarker for prognosis and may guide precision immunotherapy strategies in HCC.