Identification of heterogeneity among soft tissue sarcomas by gene expression profiles from different tumors
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BioMed Central
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Identification of heterogeneity among soft tissue sarcomas by gene expression profiles from different tumors Keith M Skubitz*1, Stefan Pambuccian2, J Carlos Manivel2 and Amy PN Skubitz2 Address: 1Department of Medicine, the University of Minnesota Medical School, Masonic Cancer Center, Minneapolis, MN 55455, USA and 2Department of Laboratory Medicine and Pathology, the University of Minnesota Medical School, Masonic Cancer Center, Minneapolis, MN 55455, USA Email: Keith M Skubitz* - [email protected]; Stefan Pambuccian - [email protected]; J Carlos Manivel - [email protected]; Amy PN Skubitz - [email protected] * Corresponding author
Published: 6 May 2008 Journal of Translational Medicine 2008, 6:23
doi:10.1186/1479-5876-6-23
Received: 30 November 2007 Accepted: 6 May 2008
This article is available from: http://www.translational-medicine.com/content/6/1/23 © 2008 Skubitz et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract 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 t
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