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Updated: May 23, 2025

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Identification of telomere-related gene subtypes and prognostic signatures in osteosarcoma.

Zhaoguang Song1, Wenyan Yu2, Xuqing Yin3

  • 1Department of West Hospital Orthopaedic Trauma, Zibo Central Hospital, Zibo, China.

Frontiers in Pharmacology
|March 12, 2025
PubMed
Summary

This study identified two osteosarcoma (OS) subtypes based on telomere-related genes (TRGs), revealing distinct immune characteristics and survival outcomes. A novel TRG signature aids in predicting OS prognosis and potential therapeutic strategies.

Keywords:
molecular subtypesosteosarcomaprognostic modeltelomeres-related genestumor microenvironment

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Area of Science:

  • Oncology
  • Genetics
  • Immunology

Background:

  • Osteosarcoma (OS) is a primary bone cancer with high metastatic potential.
  • The prognostic significance of telomere-related genes (TRGs) in OS is not well understood.
  • Identifying TRG-based subtypes can elucidate OS heterogeneity.

Purpose of the Study:

  • To identify telomere-related subtypes in osteosarcoma (OS).
  • To analyze the immune characteristics of these subtypes.
  • To develop a prognostic signature based on TRGs for OS.

Main Methods:

  • Collected OS data from TARGET and Gene Expression Omnibus databases.
  • Identified TRG-mediated subtypes and analyzed their immune characteristics.
  • Developed a prognostic signature using univariate and LASSO Cox regression, assessing its correlation with the tumor microenvironment (TME).

Main Results:

  • Discovered two TRG-defined OS subtypes (C1 and C2) with differing survival rates (C2 inferior to C1).
  • Subtype C1 exhibited increased stromal, immune, and ESTIMATE scores, with decreased tumor purity compared to C2.
  • A six-gene prognostic model (PDK2, PPARG, MORC4, SP110, TERT, MAP3K5) was established, correlating with OS prognosis and TME, with decreased expression in OS cells.

Conclusions:

  • Telomere-related genes define distinct OS subtypes with varied survival and immune profiles.
  • The developed TRG signature is a potential tool for OS prognosis and guiding TME-targeted therapies.