Transcriptome-Inferred metabolic subtypes define prognostic and immune ecosystems in osteosarcoma at single-cell resolution - Report - MDSpire

Transcriptome-Inferred metabolic subtypes define prognostic and immune ecosystems in osteosarcoma at single-cell resolution

  • By

  • Li Hu

  • Dingsheng Zhang

  • Boyang Wang

  • Qian Liu

  • Xingyu Liao

  • Feiyang Qi

  • Linxi Chen

  • Huimin Liu

  • Zhiqing Zhao

  • Haijie Liang

  • Xingyu Liu

  • Zhiye Du

  • Rui Yang

  • Yi Yang

  • Yang Wang

  • Jichuan Wang

  • June 18, 2026

  • 0 min

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Clinical Report: Metabolic Subtypes Inferred from Transcriptome Analysis Reveal Prognostic and Immune Landscapes in Osteosarcoma at the Single-Cell Level

Overview

This study identifies three distinct metabolic subtypes of osteosarcoma through transcriptome analysis, revealing significant prognostic implications. The Redox-Catabolic subtype showed a favorable survival rate compared to the other subtypes, highlighting the importance of metabolic profiling in risk stratification.

Background

Osteosarcoma is a highly aggressive bone malignancy, particularly in pediatric and adolescent populations, with variable clinical outcomes despite similar presentations. Understanding the metabolic heterogeneity of osteosarcoma can provide insights into tumor behavior and treatment responses, potentially leading to improved prognostic tools and therapeutic strategies.

Data Highlights

Subtype3-Year Overall SurvivalProgression-Free Survival
C1 (Cholesterogenic)60.0%Not specified
C2 (Redox-Catabolic)90.8%Not specified
C3 (OXPHOS-Active)61.9%Not specified

Key Findings

  • Three metabolic subtypes identified: Cholesterogenic (C1), Redox-Catabolic (C2), and OXPHOS-Active (C3).
  • C2 subtype exhibited the highest 3-year overall survival rate at 90.8%.
  • C1 and C3 subtypes had lower survival rates of 60.0% and 61.9%, respectively.
  • Single-cell RNA sequencing revealed distinct cellular origins for each subtype, aiding in understanding tumor composition.
  • Metabolic profiling can enhance risk stratification and inform therapeutic hypotheses in osteosarcoma.

Clinical Implications

The identification of metabolic subtypes in osteosarcoma underscores the potential for tailored therapeutic approaches based on metabolic profiles. Clinicians may consider integrating metabolic assessments into routine evaluations to better predict patient outcomes and guide treatment decisions.

Conclusion

This research highlights the critical role of metabolic heterogeneity in osteosarcoma, offering a framework for improved prognostic stratification and potential therapeutic targeting based on metabolic subtype.

Related Resources & Content

  1. The ASCO Post, 2020 -- Immunogenomic Profiling of Osteosarcoma
  2. The ASCO Post, 2025 -- Spatial Transcriptomics Identifies Novel Subtypes Associated With Disease Prognosis in Leiomyosarcoma
  3. Frontiers in Immunology, 2026 -- Dynamic changes in peripheral blood lymphocyte subsets predict the efficacy and prognosis of immune checkpoint inhibitors in metastatic osteosarcoma
  4. Bone Cancer, Version 2.2025, NCCN Clinical Practice Guidelines In Oncology - PubMed
  5. Journal of Neuro-Oncology — Assessing the Prognostic Significance of BRMS1+ Microglia Through Single-Cell Anoikis Regulator Patterns in the Immune Landscape of Glioblastoma
  6. Bone Cancer, Version 2.2025, NCCN Clinical Practice Guidelines In Oncology - PubMed
  7. Comparison of MAPIE versus MAP in patients with a poor response to preoperative chemotherapy for newly diagnosed high-grade osteosarcoma (EURAMOS-1): an open-label, international, randomised controlled trial - ScienceDirect
  8. Multiomics integration analysis identifies tumor cell-derived MIF as a therapeutic target and potentiates anti-PD-1 therapy in osteosarcoma | Journal for ImmunoTherapy of Cancer

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