Abstract
The most common human cancers are malignant neoplasms of the skin1,2. Incidence of cutaneous melanoma is rising especially steeply, with minimal progress in non-surgical treatment of advanced disease3,4. Despite significant effort to identify independent predictors of melanoma outcome, no accepted histopathological, molecular or immunohistochemical marker defines subsets of this neoplasm2,3. Accordingly, though melanoma is thought to present with different ‘taxonomic’ forms, these are considered part of a continuous spectrum rather than discrete entities2. Here we report the discovery of a subset of melanomas identified by mathematical analysis of gene expression in a series of samples. Remarkably, many genes underlying the classification of this subset are differentially regulated in invasive melanomas that form primitive tubular networks in vitro, a feature of some highly aggressive metastatic melanomas5. Global transcript analysis can identify unrecognized subtypes of cutaneous melanoma and predict experimentally verifiable phenotypic characteristics that may be of importance to disease progression.
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Acknowledgements
Grant support from NIH (M.E.B, M.H.) and the Australian National Health and Medical Research Council (N.H.). We thank D. Edwards for access to instrumentation used in high throughput cell migration screening; A. Cress, K. Yamada and P. Schwartzberg for discussions on cell motility and assay design; and J. Pe’er, R. Folberg, K. Daniels and J. Kan-Mitchell for donation of uveal melanoma cell lines described in ref. 5.
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Supplement 1 — Statistical methods for clustering of gene expression data and validation of cluster predictions (DOC 932 kb)
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Bittner, M., Meltzer, P., Chen, Y. et al. Molecular classification of cutaneous malignant melanoma by gene expression profiling. Nature 406, 536–540 (2000). https://doi.org/10.1038/35020115
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DOI: https://doi.org/10.1038/35020115
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