Identification of heterogeneity among soft tissue sarcomas by gene expression profiles from different tumors

Keith M Skubitz, Stefan Pambuccian, J. Carlos Carlos, Amy P Skubitz

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42 Scopus citations


The heterogeneity that soft tissue sarcomas (STS) exhibit in their clinical behavior, even within histological subtypes, complicates patient care. Histological appearance is determined by gene expression. Morphologic features are generally good predictors of biologic behavior, however, metastatic propensity, tumor growth, and response to chemotherapy may be determined by gene expression patterns that do not correlate well with morphology. One approach to identify heterogeneity is to search for genetic markers that correlate with differences in tumor behavior. Alternatively, subsets may be identified based on gene expression patterns alone, independent of knowledge of clinical outcome. We have reported gene expression patterns that distinguish two subgroups of clear cell renal carcinoma (ccRCC), and other gene expression patterns that distinguish heterogeneity of serous ovarian carcinoma (OVCA) and aggressive fibromatosis (AF). In this study, gene expression in 53 samples of STS and AF [including 16 malignant fibrous histiocytoma (MFH), 9 leiomyosarcoma, 12 liposarcoma, 4 synovial sarcoma, and 12 samples of AF] was determined at Gene Logic Inc. (Gaithersburg, MD) using Affymetrix GeneChip® U_133 arrays containing approximately 40,000 genes/ESTs. Gene expression analysis was performed with the Gene Logic Genesis Enterprise System® Software and Expressionist software. Hierarchical clustering of the STS using our three previously reported gene sets, each generated subgroups within the STS that for some subtypes correlated with histology, and also suggested the existence of subsets of MFH. All three gene sets also recognized the same two subsets of the fibromatosis samples that we had found in our earlier study of AF. These results suggest that these subgroups may have biological significance, and that these gene sets may be useful for sub-classification of STS. In addition, several genes that are targets of some anti-tumor drugs were found to be differentially expressed in particular subsets of STS.

Original languageEnglish (US)
Article number23
JournalJournal of Translational Medicine
StatePublished - May 6 2008

Bibliographical note

Funding Information:
We thank Gene Logic Inc., Gaithersburg, MD, for performing the gene expression experiments and providing the GeneExpress® Enterprise System software, and Diane Rauch and Sarah Bowell of the University of Minnesota Cancer Center's Tissue Procurement Facility for assistance in collecting and processing tissue samples. Supported in part by the Minnesota Ovarian Cancer Alliance, the National Institutes of Health, RO1CA106878 (APNS), and the University of Minnesota Supercomputing Institute.


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