Molecular classification of cutaneous malignant melanoma by gene expression profiling View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2000-08

AUTHORS

M. Bittner, P. Meltzer, Y. Chen, Y. Jiang, E. Seftor, M. Hendrix, M. Radmacher, R. Simon, Z. Yakhini, A. Ben-Dor, N. Sampas, E. Dougherty, E. Wang, F. Marincola, C. Gooden, J. Lueders, A. Glatfelter, P. Pollock, J. Carpten, E. Gillanders, D. Leja, K. Dietrich, C. Beaudry, M. Berens, D. Alberts, V. Sondak, N. Hayward, J. Trent

ABSTRACT

The most common human cancers are malignant neoplasms of the skin. Incidence of cutaneous melanoma is rising especially steeply, with minimal progress in non-surgical treatment of advanced disease. Despite significant effort to identify independent predictors of melanoma outcome, no accepted histopathological, molecular or immunohistochemical marker defines subsets of this neoplasm. Accordingly, though melanoma is thought to present with different 'taxonomic' forms, these are considered part of a continuous spectrum rather than discrete entities. 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 melanomas. Global transcript analysis can identify unrecognized subtypes of cutaneous melanoma and predict experimentally verifiable phenotypic characteristics that may be of importance to disease progression. More... »

PAGES

536

References to SciGraph publications

Journal

TITLE

Nature

ISSUE

6795

VOLUME

406

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/35020115

    DOI

    http://dx.doi.org/10.1038/35020115

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1039076321

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/10952317


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