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April 15, 2026International Journal of Molecular Sciences0 citationsOpen Access

Multi-Modal Analysis of Programmed Cell Death Identifies Biomarkers and Informs Prognosis in Osteosarcoma

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XZXinyi ZouYRYuanfang Ru

Key Points

  • The aim was to identify molecular subtypes of osteosarcoma and their prognostic significance by analyzing programmed cell death pathways.
  • Integrated PCD-related gene signatures using consensus clustering.
  • Performed differential expression and functional enrichment analyses.
  • Conducted protein–protein interaction (PPI) network analyses to identify subtype-specific associations.
  • Implemented comparative immune profiling and clinical characterization to refine subgroup identities.
  • Developed a prognostic risk model based on five pivotal genes and metastasis status.
  • Four distinct osteosarcoma subtypes with varying prognostic outcomes were identified.
  • Subtype-specific programmed cell death pathways, such as apoptosis and pyroptosis, were associated with the molecular subtypes.
  • A prognostic risk model showed superior predictive performance in both training and validation cohorts.
  • The findings provide a foundation for precision risk stratification and tailored therapeutic strategies in osteosarcoma.

Abstract

Osteosarcoma (OS), the most prevalent primary malignant bone tumor with a dismal prognosis, exhibits significant heterogeneity in programmed cell death (PCD) pathways, but its subtype-specific functional mechanisms remain poorly characterized. This study integrated PCD-related gene signatures to delineate molecular subtypes in OS via consensus clustering, successfully defining four distinct subtypes with divergent prognostic outcomes and immune microenvironments. Differential expression, functional enrichment, and protein–protein interaction (PPI) network analyses revealed subtype-specific PCD pathway associations (e.g., lysosome-dependent cell death, apoptosis, pyroptosis and anoikis), while comparative immune profiling and clinical characterization further refined subgroup identities. A robust prognostic risk model incorporating five pivotal genes (SERPINE2, CBS, SQLE, UBE2D4, and S100A13) and metastasis status demonstrated superior predictive performance in both training and external validation cohorts. These findings not only elucidate the functional architecture of PCD across OS molecular subtypes but also establish a clinically actionable model for precision risk stratification and tailored therapeutic strategies.

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Cite This Study

Zou et al. (2026) studied this question.

synapsesocial.com/papers/69df2bcae4eeef8a2a6b0b6ahttps://doi.org/10.3390/ijms27083431
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