The Identification of LA-tumor associated macrophages in immune modulation via amyloid-beta precursor protein/CD74 signal pathway in gastric cancer: a predictive module and machine learning

Background: Tumor-associated macrophages (TAMs) play a critical role in Cancer immune microenvironment, modulating immune evasion. The prognostic role of TAMs gives insights into the immune landscape and therapeutic targets in gastric Cancer (GC).

Methods: GC microenvironment was analyzed via single-cell and bulk RNA-seq data from public databases. TAM subtypes were then identified via dimensionality reduction and annotation under quality control. TAM differentiation and function were evaluated by pseudo-time analysis, cell communication, molecular docking, and key gene enrichment. A predictive model based on LA-TAM was established. Amyloid-β precursor protein (APP) expression level and its effect on macrophage programmed death-1 (PD-1) expression was validated in vitro.

Results: In GC microenvironment, epithelial cells and fibroblasts were downregulated, while B cells, CD8⁺ T cells and myeloid cells were enriched. Among TAM subtypes, LA-TAM exhibited the potential of differentiation, metabolic reprogramming, and high plasticity. When LA-TAM interacts with endothelial cells, APP/Collagen pathway was activated, in which PD-1 expression was up-regulated by APP/CD74 activation. The LA-TAM-based predictive model showed significant performance among multiple cohorts (C-index >0.5, HR = 1.63, p<0.001). APP positively correlated with PD-1 expression. In GC THP-1 monocytes, APP was enriched and stimulated PD-1 expression.

Conclusion: LA-TAM plays a key role in immune suppression and metabolic regulation in GC. Its key genes form a high-precision prognosis model, and endothelial cell-expressed APP may promote immune evasion by enhancing macrophage PD-1 expression, suggesting a potential target for immunotherapy.

gastric cancer; immune evasion; machine learning; predictive biomarkers; tumor-associated macrophages.