International Orthopaedics

, Volume 35, Issue 3, pp 401–411 | Cite as

Microarray analysis identifies distinct gene expression profiles associated with histological subtype in human osteosarcoma

  • Bernd Kubista
  • Florian Klinglmueller
  • Martin Bilban
  • Martin Pfeiffer
  • Richard Lass
  • Alexander Giurea
  • Phillipp T. Funovics
  • Cyril Toma
  • Martin Dominkus
  • Rainer Kotz
  • Theresia Thalhammer
  • Klemens Trieb
  • Teresa Zettl
  • Christian F. Singer
Original Paper


Osteosarcoma is the most common primary malignant bone tumour. Currently osteosarcoma classification is based on histological appearance. It was the aim of this study to use a more systematic approach to osteosarcoma classification based on gene expression analysis and to identify subtype specific differentially expressed genes. We analysed the global gene expression profiles of ten osteosarcoma samples using Affymetrix U133A arrays (five osteoblastic and five non-osteoblastic osteosarcoma patients). Differential gene expression analysis yielded 75 genes up-regulated and 97 genes down-regulated in osteoblastic versus non-osteoblastic osteosarcoma samples, respectively. These included genes involved in cell growth, chemotherapy resistance, angiogenesis, steroid- and neuropeptide hormone receptor activity, acute-phase response and serotonin receptor activity and members of the Wnt/ß-catenin pathway and many others. Furthermore, we validated the highly differential expression of six genes including angiopoietin 1, IGFBP3, ferredoxin 1, BMP, decorin, and fibulin 1 in osteoblastic osteosarcoma relative to non-osteoblastic osteosarcoma. Our results show the utility of gene expression analysis to study osteosarcoma subtypes, and we identified several genes that may play a role as potential therapeutic targets in the future.


Osteosarcoma Osteosarcoma Cell Osteosarcoma Patient Osteoblastic Osteosarcoma Osteosarcoma Sample 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Conflicts of interest statement

None declared.


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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Bernd Kubista
    • 1
  • Florian Klinglmueller
    • 2
  • Martin Bilban
    • 2
  • Martin Pfeiffer
    • 1
  • Richard Lass
    • 1
  • Alexander Giurea
    • 1
  • Phillipp T. Funovics
    • 1
  • Cyril Toma
    • 1
  • Martin Dominkus
    • 1
  • Rainer Kotz
    • 1
  • Theresia Thalhammer
    • 3
  • Klemens Trieb
    • 4
  • Teresa Zettl
    • 1
  • Christian F. Singer
    • 5
  1. 1.Department of OrthopedicsMedical University of ViennaViennaAustria
  2. 2.Department of Laboratory Medicine and Ludwig Boltzmann Institute for Clinical and Experimental OncologyMedical University of ViennaViennaAustria
  3. 3.Institute of Pathophysiology, Center for Physiology, Pathophysiology and ImmunologyMedical University of ViennaViennaAustria
  4. 4.Department of OrthopedicsKlinikum Kreuzschwestern WelsWelsAustria
  5. 5.Division of Special Gynecology, Department of OB/GYNMedical University of ViennaViennaAustria

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