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Heterogeneity of metastatic behavior among high-grade pleomorphic soft tissue sarcomas identified by gene expression analysis.

10082 Background: Heterogeneity in clinical behavior of soft tissue sarcomas (STS), even within histological subtypes, complicates treatment. Metastatic propensity may be determined by gene expression patterns that do not correlate well with morphology. In earlier studies, we identified gene expression patterns that distinguished two subsets of clear cell renal cell carcinoma (ccRCC), serous ovarian carcinoma (OVCA), and aggressive fibromatosis (AF). In this study, we combined these three gene sets into one "pooled gene set" and used a set of clinically well defined STS for analysis.


METHODS
Gene expression patterns for 73 samples of high-grade STS were examined using cDNA microarray slides containing ~16,000 unique UniGene clusters. Clinical data, such as time to development of metastatic disease, was linked to each sample.


RESULTS
Half of the genes in the "pooled gene set" were represented in the current data, and these were combined to form a composite set of genes. Hierarchical clustering using this composite gene set suggested the existence of subsets of the STS samples. Kaplan-Meier analysis revealed differences in the time to development of metastatic disease between the clusters defined by the first branch point of the clustering dendrogram (p=0.01), and also among the four different clusters defined by the second branch points (p=0.001).


CONCLUSIONS
This approach may allow the identification of more than two subsets of high-grade STS, each with distinct clinical behavior, and may be useful to stratify STS in clinical trials and in patient management.