SPP1 Macrophages Drive Gastric Cancer Progression Through SERPINE1 Stromal Remodeling
Single-cell and spatial transcriptomics pinpoint a macrophage subtype and SERPINE1 as key drivers of poor outcomes in gastric cancer.
Summary
Researchers integrated single-cell RNA sequencing, spatial transcriptomics, and bulk tumor data to map macrophage diversity in gastric cancer. They identified five macrophage subtypes, with the macro_SPP1 subtype strongly linked to worse survival. Using machine learning and Cox regression, SERPINE1 emerged as the top prognostic gene connecting SPP1 macrophages to stromal remodeling. Spatially, SERPINE1-high tumor regions were enriched with fibroblasts, blood vessel components, and TGF-β and hypoxia signaling. Knocking down SERPINE1 in gastric cancer cell lines significantly reduced proliferation, colony formation, migration, and invasion. These findings suggest SERPINE1 bridges tumor-promoting macrophage activity and the remodeled stromal environment that enables cancer spread.
Detailed Summary
Gastric cancer remains one of the leading causes of cancer-related death worldwide, partly because the tumor microenvironment (TME) — particularly its immune and stromal components — actively facilitates tumor progression. Macrophages within the TME are highly diverse and context-dependent, yet which specific macrophage states drive poor outcomes and through what molecular intermediaries they reshape the surrounding stroma has remained poorly understood. This study used a multi-modal transcriptomic approach to address these gaps with granular, spatially resolved resolution.
The researchers integrated single-cell RNA sequencing data from the public dataset GSE183904, spatial transcriptomic data from GSE251950, and bulk tumor expression data from TCGA-STAD. Unsupervised clustering resolved five distinct macrophage subclusters within gastric cancer tissue: macro_SPP1, macro_IL1B, macro_C3_CX3CR1, macro_FCN1, and a resident-like cluster. Cell–cell communication analysis revealed dramatically intensified intercellular signaling in tumor versus normal tissue, with particularly prominent changes in MIF, COLLAGEN, FN1, LAMININ, and SPP1 signaling pathways — all known mediators of matrix remodeling and immune suppression.
Survival analysis demonstrated that macro_SPP1 and macro_IL1B macrophage signatures were significantly associated with shorter overall survival in gastric cancer patients, while macro_C3_CX3CR1 was linked to more favorable outcomes. To identify the molecular connector between macro_SPP1 and stromal remodeling, the team intersected macro_SPP1 marker genes with tumor-associated differentially expressed genes from TCGA-STAD. This candidate list was then subjected to Cox proportional hazards regression and multiple machine learning algorithms including LASSO, random forest, and support vector machine approaches. SERPINE1 (also known as PAI-1, plasminogen activator inhibitor-1) consistently emerged as the top-ranked prognostic candidate across all methods. High SERPINE1 expression was independently associated with poor overall survival and with stromal, myeloid, and vascular transcriptional signatures in bulk tumor data.
Spatial transcriptomic analysis provided crucial tissue-level context: SERPINE1-high regions within gastric tumors were specifically co-enriched for fibroblast- and endothelial-related gene programs and for pathway signatures of TGF-β signaling, hypoxia response, inflammatory activity, and extracellular matrix (ECM) remodeling. This spatial co-localization pattern suggests SERPINE1 operates at the interface of macrophage-driven immune activity and the stromal compartment that surrounds and supports tumor cells. Virtual perturbation modeling further indicated that SERPINE1 may influence myeloid and matrix-related transcriptional networks beyond its expression in tumor epithelium alone.
Functional validation in gastric cancer cell lines confirmed the biological relevance of SERPINE1. Stable knockdown of SERPINE1 significantly reduced cell proliferation and colony formation capacity, and substantially impaired cell migration and invasion in transwell assays. These in vitro findings align with SERPINE1's known roles as a protease inhibitor affecting ECM remodeling and its emerging functions in regulating tumor cell plasticity. Together, the multi-omics data and functional experiments position SERPINE1 as a central node linking macro_SPP1 macrophage biology, stromal remodeling programs, and intrinsic tumor cell aggressiveness — making it a compelling candidate biomarker and potential therapeutic target in gastric cancer.
Key Findings
- Five macrophage subclusters resolved by single-cell RNA sequencing; macro_SPP1 and macro_IL1B were independently associated with shorter overall survival in TCGA-STAD gastric cancer patients
- Macro_C3_CX3CR1 macrophage signature was linked to significantly more favorable survival outcomes compared to SPP1 and IL1B subtypes
- Cell–cell communication analysis showed intensified MIF, COLLAGEN, FN1, LAMININ, and SPP1 pathway signaling in tumor versus normal gastric tissue
- SERPINE1 ranked as the top prognostic gene across Cox regression and multiple machine learning models (LASSO, random forest, support vector machine) applied to macro_SPP1 marker and TCGA-STAD differentially expressed gene intersections
- Spatial transcriptomics localized SERPINE1-high tumor regions to microenvironments enriched for fibroblast and endothelial programs and for TGF-β, hypoxia, inflammatory, and ECM remodeling pathway signatures
- SERPINE1 knockdown in gastric cancer cell lines significantly reduced proliferation, colony formation, migration, and invasion in vitro
- High SERPINE1 expression in bulk TCGA-STAD data correlated with stromal, myeloid, and vascular transcriptional features, supporting its role as a TME-remodeling hub gene
Methodology
The study used publicly available single-cell RNA sequencing data (GSE183904) and spatial transcriptomic data (GSE251950) combined with TCGA-STAD bulk RNA expression and survival data. Macrophage subclusters were identified by unsupervised graph-based clustering, and intercellular communication was modeled computationally. Prognostic gene identification used Cox proportional hazards regression combined with multiple machine learning algorithms including LASSO, random forest, and support vector machine applied to the intersection of macro_SPP1 markers and tumor-associated differentially expressed genes. Functional validation was performed via SERPINE1 knockdown in gastric cancer cell lines with proliferation, colony formation, migration, and invasion assays.
Study Limitations
This study is primarily computational and observational, relying on publicly available datasets rather than a prospectively collected, independently validated patient cohort, which limits causal interpretation of survival associations. The functional experiments were conducted only in cell lines, with no in vivo tumor model data provided to confirm SERPINE1's role in stromal remodeling in a living system. The authors acknowledge that the precise mechanism by which macro_SPP1 macrophages regulate SERPINE1 expression in neighboring stromal cells versus tumor cells remains to be experimentally established. No conflicts of interest are declared.
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