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Classification of Clear-Cell Sarcoma as a Subtype of Melanoma by Genomic Profiling

Neil H. Segal, Paul Pavlidis, William S. Noble, Cristina R. Antonescu, Agnes Viale, Umadevi V. Wesley, Klaus Busam, Humilidad Gallardo, Dianne DeSantis, Murray F. Brennan, Carlos Cordon-Cardo, Jedd D. Wolchok, Alan N. Houghton

From the Memorial Sloan-Kettering Cancer Center and Columbia Genome Center, Columbia University, New York, NY.

Address reprint requests to N.H. Segal, MD, PhD, c/o Alan N. Houghton MD, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10021; email: segaln01{at}med.nyu.edu.

Purpose: To develop a genome-based classification scheme for clear-cell sarcoma (CCS), also known as melanoma of soft parts (MSP), which would have implications for diagnosis and treatment. This tumor displays characteristic features of soft tissue sarcoma (STS), including deep soft tissue primary location and a characteristic translocation, t(12;22)(q13;q12), involving EWS and ATF1 genes. CCS/MSP also has typical melanoma features, including immunoreactivity for S100 and HMB45, pigmentation, MITF-M expression, and a propensity for regional lymph node metastases.

Materials and Methods: RNA samples from 21 cell lines and 60 pathologically confirmed cases of STS, melanoma, and CCS/MSP were examined using the U95A GeneChip (Affymetrix, Santa Clara, CA). Hierarchical cluster analysis, principal component analysis, and support vector machine (SVM) analysis exploited genomic correlations within the data to classify CCS/MSP.

Results: Unsupervised analyses demonstrated a clear distinction between STS and melanoma and, furthermore, showed that CCS/MSP cluster with the melanomas as a distinct group. A supervised SVM learning approach further validated this finding and provided a user-independent approach to diagnosis. Genes of interest that discriminate CCS/MSP included those encoding melanocyte differentiation antigens, MITF, SOX10, ERBB3, and FGFR1.

Conclusion: Gene expression profiles support the classification of CCS/MSP as a distinct genomic subtype of melanoma. Analysis of these gene profiles using the SVM may be an important diagnostic tool. Genomic analysis identified potential targets for the development of therapeutic strategies in the treatment of this disease.

Supported in part by the Etta Weinheim Memorial Fund, New York, NY (J.D.W.); National Institutes of Health, Bethesda, MD, grant no. CA-47179 (M.F.B. and A.N.H.); Swim Across America, New York, NY; the Kennedy Family Fund, Naples, FL; and National Science Foundation, Arlington, VA, grant no. IIS-0093302 (W.S.N.).

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