ArticleDiscover oncology2025
A multi-type programmed cell death gene signature predicts survival and reveals therapeutic targets in osteosarcoma.
Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Multi-Modal Analysis of Programmed Cell Death Identifies Biomarkers and Informs Prognosis in Osteosarcoma.International journal of molecular sciences · 2026Article
- Pan-cancer analysis of role of LOXL4 and experiment validation in osteosarcoma.Discover oncology · 2025Article
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Authors and funding
1 author.
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Abstract
backgroundOsteosarcoma (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.
methodsTranscriptomic 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.
resultsThere 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.
conclusionThis 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.
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