Abstract
BACKGROUND: Osteosarcoma (OS) is an aggressive bone tumor with poor outcomes in advanced stages. Programmed cell death (PCD) plays a crucial role in tumor biology, but the prognostic value of integrating multiple PCD-related genes in OS remains underexplored. METHODS: Transcriptomic data from GEO and clinical data from TARGET were analyzed. Functional enrichment, N6-methyladenosine (m6A)-related genes analysis and immune checkpoint analyses were performed. Genes related to 18 types of PCD were intersected with OS-specific differentially expressed genes. Prognostic genes were identified by Kaplan-Meier and Cox regression. A LASSO model was developed to construct a survival prediction signature. Single-cell RNA-seq data were used to explore gene expression across cell types. RESULTS: There are 781 differentially expressed genes totally. M6A-related genes including ALKBH3, CBLL1 and immune checkpoints including HAVCR2, PDCD1 showed differential expression in OS. Twelve PCD-related genes were significantly associated with OS survival. A four-gene (FUCA1, GM2A, MAN2B1, COL13A1) prognostic model was established, showing strong predictive performance (3-year AUC = 0.801; 5-year AUC = 0.842). Lysosome-dependent cell death, apoptosis and anoikis emerged as key PCD pathways in OS. Single-cell analysis revealed COL13A1 expression in malignant cells while GM2A and FUCA1 were enriched in macrophages. CONCLUSION: This study identifies a robust PCD-related prognostic model for OS and highlights key genes and pathways involved in tumor progression. The present findings determine potential biomarkers and therapeutic targets to improve OS prognosis and treatment.