9574 Background: Soft tissue sarcomas (STS) exhibit heterogeneity in their clinical behavior, even within histological subtypes. Histological appearance is determined by gene expression. 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 markers that correlate with differences in tumor behavior. Alternatively, subsets may be identified based on gene expression patterns independent of knowledge of clinical outcome. We have reported gene expression patterns that distinguish two broad classes of clear cell renal carcinoma (ccRCC) independent of histological appearance, and other patterns that can distinguish heterogeneity of serous ovarian carcinoma (OVCA). Methods: In this study, gene expression in 41 samples of STS (including malignant fibrous histiocytoma (MFH), leiomyosarcoma, liposarcoma, and synovial sarcoma), 12 samples of fibromatosis, and 17 normal tissues 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. Results: Hierarchical clustering using two gene sets, one that distinguished two subsets of ccRCC, and a second set that distinguished two subsets of OVCA, both generated subgroups within the STS that for some, but not all, subtypes correlated with histology, and also suggested the existence of subsets of MFH. Both gene sets also identified the same two subsets of the fibromatosis samples. In addition, genes expressed uniquely in MFH, leiomyosarcomas, and liposarcomas among these and 512 samples from 17 other normal tissue types were identified. Conclusions: The ability to sub-classify histological subtypes of STS, including identifying possible subsets of MFH, using gene sets derived from studies of two different carcinomas suggests that these subgroups may have biological significance. Some of the genes identified as over-expressed in particular subsets of STS compared with a variety of normal tissues may reflect possible targets to which anti-tumor therapy could be directed, and may also be useful for sub-classification of STS. No significant financial relationships to disclose.
CT Perfusion as an Imaging Biomarker in Monitoring Response to Neoadjuvant Bevacizumab and Radiation in Soft-Tissue Sarcomas: Comparison With Tumor Morphology, Circulating and Tumor Biomarkers, and Gene Expression
