An SPP1-centered immune-parenchymal communication axis links macrophage heterogeneity to ovarian cancer prognosis

Immune and malignant epithelial cells shape each other through ligand-receptor signaling in ovarian cancer. SPP1 interacts with CD44 and several integrins, but its cellular organization and clinical relevance remain unclear.

We integrated GSE184880 scRNA-seq data with TCGA-OV and three independent cohorts. Single-cell clustering, CNV inference, and cell communication analysis were used to characterize macrophage states and SPP1-related signaling. Based on the SPP1 ligand-receptor network identified by CellChat, an 11-gene set comprising SPP1 and its CD44/integrin receptor components was constructed and subsequently used for molecular subtyping. Four machine learning models were compared for prognostic prediction. PI3 was subsequently silenced in ES-2 and SKOV3 cells. SPP1 expression and secretion, cell proliferation, wound closure, migration, invasion, xenograft growth, and macrophage phenotypes after coculture were then evaluated.

Four macrophage states were identified: Resident Macro, Inflammatory Macro, SPP1+ TAM, and Activated Macro. Cell communication was extensively reorganized in ovarian tumors. SPP1+ TAM occupied a central position in the SPP1 network and communicated with malignant epithelial cells, fibroblasts, endothelial cells, and other macrophage populations through SPP1-CD44 and SPP1-integrin interactions. SPP1-related genes separated patients into SPP1-High and SPP1-Low subtypes. The SPP1-High subtype showed stronger immune- and cytokine-related activity and poorer overall survival. Among the four machine learning models, GBM-Cox achieved the highest C-index of 0.768 and maintained prognostic stratification across three independent cohorts. PI3 also ranked highly in several models. Silencing PI3 in tumor cells increased TNF, IL1B, CXCL10, and CD86 expression in cocultured macrophages, while reducing CD163, MRC1, CCL18, and IL10. Consistently, TNF-α and IL-12p70 levels increased, whereas IL-10 and CCL18 levels decreased. PI3 silencing reduced SPP1 mRNA expression and secretion and suppressed ovarian cancer cell proliferation, wound closure, migration, and invasion. Stable PI3 knockdown also delayed ES-2 xenograft growth and reduced terminal tumor volume and weight.

The SPP1-associated ligand-receptor network represents an immune-parenchymal communication axis linking macrophages with malignant epithelial and stromal cells in ovarian cancer. This network captures differences in immune state and clinical outcome and supports both molecular classification and prognostic assessment. PI3 may contribute to tumor cell-mediated regulation of macrophage phenotype and could serve as a candidate biomarker or intervention target. PI3 may promote ovarian cancer progression while contributing to tumor-cell-derived SPP1 production and macrophage regulation, supporting its potential value as a candidate biomarker and therapeutic target.