Classification of clear-cell sarcoma as a subtype of melanoma by genomic profiling Journal Article

Authors: Segal, N. H.; Pavlidis, P.; Noble, W. S.; Antonescu, C. R.; Viale, A.; Wesley, U. V.; Busam, K.; Gallardo, H.; Desantis, D.; Brennan, M. F.; Cordon-Cardo, C.; Wolchok, J. D.; Houghton, A. N.
Article Title: Classification of clear-cell sarcoma as a subtype of melanoma by genomic profiling
Abstract: 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 immunoreactrvity 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. © 2003 by American Society of Clinical Oncology.
Keywords: immunohistochemistry; controlled study; protein expression; human cell; genetics; clinical feature; lymph node metastasis; tumor localization; melanoma; cluster analysis; classification; gene expression profiling; melanocyte; diagnosis, differential; differential diagnosis; cell differentiation; pathology; tumor cells, cultured; validation study; immunoreactivity; algorithms; tumor antigen; pigmentation; correlation analysis; antigens, neoplasm; cell culture; algorithm; oligonucleotide array sequence analysis; artificial intelligence; cancer cell; soft tissue sarcoma; genomics; protein s 100; dna microarray; cancer classification; epidermal growth factor receptor 3; microphthalmia associated transcription factor; rna binding protein ews; chromosome 12q; soft tissue neoplasms; soft tissue tumor; fibroblast growth factor receptor 1; clear cell sarcoma; sarcoma, clear cell; chromosome 13q; principal component analysis; activating transcription factor 1; support vector machine; chromosome translocation 22; transcription factor sox10; humans; human; priority journal; article; chromosome translocation 12
Journal Title: Journal of Clinical Oncology
Volume: 21
Issue: 9
ISSN: 0732-183X
Publisher: American Society of Clinical Oncology  
Date Published: 2003-05-01
Start Page: 1775
End Page: 1781
Language: English
DOI: 10.1200/jco.2003.10.108
PUBMED: 12721254
PROVIDER: scopus
Notes: Export Date: 12 September 2014 -- Source: Scopus
Altmetric Score
MSK Authors
  1. Murray F Brennan
    756 Brennan
  2. Jedd D Wolchok
    637 Wolchok
  3. Neil Howard Segal
    100 Segal
  4. Cristina R Antonescu
    606 Antonescu
  5. Agnes Viale
    205 Viale
  6. Klaus J Busam
    535 Busam
  7. Alan N Houghton
    264 Houghton