Global Protein-expression Analysis of Bone and Soft Tissue Sarcomas

  • Akira Kawai
  • Tadashi Kondo
  • Yoshiyuki Suehara
  • Kazutaka Kikuta
  • Setsuo Hirohashi
Symposium: Molecular Genetics in Sarcoma


Analysis of global protein expression, an approach known as expression proteomics, can offer important clues for understanding tumor biology that cannot be obtained by other approaches (e.g., genome or transcriptome analysis). Using two-dimensional difference gel electrophoresis (2D-DIGE) and mass spectrometry, we performed global protein expression studies of bone and soft tissue sarcomas to develop novel diagnostic and therapeutic biomarkers and allow molecular classification of the tumors. Among 1500 protein variants identified in the two-dimensional gel, 67 proteins correctly distinguished the eight subtypes of 99 histologically classified soft tissue sarcomas. Hierarchical clustering demonstrated leiomyosarcoma and MFH shared a similar protein expression profile, and clear cell sarcoma, synovial sarcoma, and MPNST could be grouped according to their protein expression patterns. Pleomorphic leiomyosarcoma and MFH showed similar tropomyosin isoform expression patterns. Patients with gastrointestinal stromal tumors expressing pfetin protein had better survival than those whose tumors lacked it. We identified 10 protein spots associated with the chemosensitivity of osteosarcoma to preoperative chemotherapy. These 10 spots could be new diagnostic and prognostic markers for osteosarcoma and new therapeutic targets for the disease. Proteomic analysis using 2D-DIGE provides novel information on the biology of bone and soft tissue sarcomas that could be used to diagnosis and treat these tumors.

Level of Evidence: Level II, diagnostic study. See the Guidelines for Authors for a complete description of levels of evidence.


Osteosarcoma Soft Tissue Sarcoma Protein Spot Synovial Sarcoma Malignant Peripheral Nerve Sheath Tumor 
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.



We thank Robert Nakayama, Eisuke Kobayashi, and Ako Hosono for helpful and stimulating discussions and Misuzu Mori for technical assistance.


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Copyright information

© The Association of Bone and Joint Surgeons 2008

Authors and Affiliations

  • Akira Kawai
    • 1
  • Tadashi Kondo
    • 2
  • Yoshiyuki Suehara
    • 1
    • 3
  • Kazutaka Kikuta
    • 1
  • Setsuo Hirohashi
    • 2
  1. 1.Division of Orthopaedic SurgeryNational Cancer Center HospitalTokyoJapan
  2. 2.Proteome Bioinformatics ProjectNational Cancer Center Research InstituteTokyoJapan
  3. 3.Department of Orthopaedic SurgeryJuntendo University School of MedicineTokyoJapan

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