The gene expression signatures of melanoma progression

Abstract

Because of the paucity of available tissue, little information has previously been available regarding the gene expression profiles of primary melanomas. To understand the molecular basis of melanoma progression, we compared the gene expression profiles of a series of nevi, primary melanomas, and melanoma metastases. We found that metastatic melanomas exhibit two dichotomous patterns of gene expression, which unexpectedly reflect gene expression differences already apparent in comparing laser-capture microdissected radial and vertical phases of a large primary melanoma. Unsupervised hierarchical clustering accurately separated nevi and primary melanomas. Multiclass significance analysis of microarrays comparing normal skin, nevi, primary melanomas, and the two types of metastatic melanoma identified 2,602 transcripts that significantly correlated with sample class. These results suggest that melanoma pathogenesis can be understood as a series of distinct molecular events. The gene expression signatures identified here provide the basis for developing new diagnostics and targeting therapies for patients with malignant melanoma.

Fig. 1.

Gene expression analysis of the radial and vertical growth phases of primary melanoma. Photograph (A) and photomicrograph (B) of PM09, depicting areas of radial and vertical growth used for laser capture microdissection. (C) List of sam genes shows that many cell adhesion receptors and ESTs are lost in the vertical phase (see Table 1, which is published as supporting information on the PNAS web site, for full list of gene names). Photomicrographs of CDH3 (D) and MMP10 (E) immunostaining in radial growth phase versus vertical growth phase melanoma, with high-power views of the radial growth phase (Left) and vertical growth phase (Right).

Fig. 2.

Molecular division of metastatic melanoma into two subtypes. (A) Unsupervised hierarchical clustering of metastatic melanoma defines molecular subtypes I and II. (B) Genes identified by sam as lost in the PM09 gene set assessed in the metastatic melanoma dataset. (C) Expression of the PM09 gene set comparing the primary tumor and metastasis within a single patient, MM14. See Data Sets 1-6.

Fig. 4.

Multiclass sam applied to skin, nevi, and primary and metastatic melanoma subtypes predicts 2,602 genes with only 1.6 predicted false-positives able to distinguish among these tissue types. The data table using the 2,602 genes from multiclass analysis was used for supervised hierarchical clustering to facilitate data display. (A) Cluster map of 2,602 genes able to distinguish tissue types. (B) Gene expression nodes particular to each tissue type are highlighted. (B.1) Skin gene expression (B.2) Melanocytic gene expression. (B.3) Melanoma gene expression. (B.4) Metastatic melanoma gene expression. (B.5) Expression lost in metastatic melanoma. See Data Sets 10 and 11.

Fig. 3.

Unsupervised hierarchical cluster analysis applied to nevus and primary melanoma data set. (A) Overall gene expression sample cluster tree shows that nevi and primary melanomas are readily distinguished. (B) Genes more highly expressed in primary melanoma (nodes showing CXCL1 and PRAME) are contrasted with markers of melanocytic differentiation (nodes showing S100B and MLANA). See Data Sets 7-9.