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Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors
Published on: February 27, 2015
Proteomic signatures corresponding to histological classification and grading of soft-tissue sarcomas
Yoshiyuki Suehara1, Tadashi Kondo, Kiyonaga Fujii
1Proteome Bioinformatics Project, National Cancer Center Research Institute, Tokyo, Japan.
Abstract:
We performed a global protein expression study on soft-tissue sarcoma in order to develop novel diagnostic biomarkers and allow molecular classification. 2-D difference gel electrophoresis was used to generate the global protein expression profiles of 80 soft-tissue sarcoma samples with seven different histological backgrounds. We found that 67 protein spots distinguished the subtypes of soft-tissue sarcoma. Hierarchical clustering with these 67 protein spots resulted in the grouping of all 80 sarcoma samples corresponding to the histological classification. We found that the expression pattern of tropomyosin isoforms was different in conventional and pleomorphic leiomyosarcomas. We also identified five proteins, including alpha-1-antitrypsin, alpha-actinin 1, HSP27, and elongation factor 2, that could differentiate between malignant fibrous histiocytomas and leiomyosarcomas in grade III into low-risk and high-risk groups, which differed significantly with respect to survival. These results establish proteomics as a powerful tool to develop novel biomarkers for diagnosis and molecular classification of soft-tissue sarcomas. Identification of proteins associated with survival in grade III sarcoma will allow delineation of a high-risk group that may benefit from adjuvant therapy and the exclusion of low-risk patients in whom additional therapies are unlikely to exhibit clinical benefit.

