Differential gene expression profiling of primary cutaneous melanoma and sentinel lymph node metastases.

Limited understanding of molecular mechanisms of metastasis in melanoma contributes to the absence of effective treatments. Increased knowledge of alterations in genes that underpin critical molecular events that lead to metastasis is essential. We have investigated the gene expression profiles of primary melanomas and melanoma metastases in sentinel lymph nodes. A total of 19 samples (10 primary melanomas and 9 sentinel lymph node metastases) were evaluated. Melanoma cells were dissected from tissue blocks. Total mRNA was isolated, amplified, and labeled using an Ambion Recover All Total Nucleic Acid Isolation kit, Nu-GEN WT-Ovation formalin-fixed, paraffin-embedded RNA Amplification System, and FL-Ovation cDNA Biotin Module V2, respectively. Samples were hybridized to the Affymetrix Gene Chip Human U133 Plus 2.0 Array. Data were analyzed using Partek Genomics Suite Version 6.4. Genes selected showed ≥2-fold difference in expression and P<5.00E-2. Validation studies used standard immunohistochemical assays. Hierarchical clustering disclosed two distinct groups: 10 primary melanomas and 9 sentinel lymph node metastases. Gene expression analysis identified 576 genes that showed significant differential expression. Most differences reflected decreased gene expression in metastases relative to primaries. Reduced gene expression in primaries was less frequent and less dramatic. Genes significantly increased or decreased in sentinel lymph node metastases were active in cell adhesion/structural integrity, tumor suppression, cell cycle regulation, and apoptosis. Validation studies indicate that MAGEC1 (melanoma antigen family C1) and FCRL1 (Fc receptor-like 1) are involved in melanoma progression. There are striking differential gene expression patterns between primary and nodally metastatic melanomas. Similar findings were seen with autologous paired primary melanomas and sentinel lymph node metastases, supporting involvement of these gene alterations in evolution of metastases. With further study, it may be possible to determine the exact sequence of molecular events that underlie melanoma metastases.

Molecular classification of melanomas and nevi using gene expression microarray signatures and formalin-fixed and paraffin-embedded tissue.

Melanoma may be difficult to identify histologically and relatively high rates of misdiagnosis leads to many malpractice claims. Currently separation of melanomas from nevi is based primarily on light microscopic interpretation of hematoxylin and eosin stained sections with limited assistance from immunohistology. To increase the accuracy of discrimination of benign and malignant melanocytic lesions we identified DNA microarray-derived gene expression profiles of different melanocytic lesions and evaluated the performance of these gene signatures as molecular diagnostic tools in the molecular classification and separation of melanomas and nevi. Melanocyte-derived cells were isolated by laser capture microdissection from 165 formalin-fixed and paraffin-embedded melanocytic nevi and melanoma tissue sections. RNA was isolated, amplified, labeled, and hybridized to a custom DNA microarray. In all 120 samples were used to identify differentially expressed genes and generate a gene expression classifier capable of distinguishing between melanomas and nevi. These classifiers were tested by the leave-one-out method and in a blinded study. RT-PCR verified the results. Unsupervised hierarchical clustering identified two distinct lesional groups that closely correlated with the histopathologically identified melanomas and nevi. Analysis of gene expression levels identified 36 significant differentially expressed genes. In comparison with nevi, melanomas expressed higher levels of genes promoting signal transduction, transcription, and cell growth. In contrast, expression of L1CAM (homolog) was reduced in melanomas relative to nevi. Genes differentially expressed in melanomas and nevi, on the basis of molecular signal, sub classified a group of unknown melanocytic lesions as melanomas or nevi and had high concordance rates with histopathology. Gene signatures established using DNA microarray gene expression profiling can distinguish melanomas from nevi, indicating the feasibility of using molecular classification as a supplement to standard histology. Our successful use of a standard formalin-fixed and paraffin-embedded tissue further supports the practicability of combining molecular diagnostic testing with histopathology in evaluation of difficult melanocytic lesions.