BACKGROUND: Gene expression profiling has revolutionized our ability to 
molecularly classify primary human tumors and significantly enhanced the 
development of novel tumor markers and therapies; however, progress in the 
diagnosis and treatment of melanoma over the past 3 decades has been limited, 
and there is currently no approved therapy that significantly extends lifespan 
in patients with advanced disease. Profiling studies of melanoma to date have 
been inconsistent due to the heterogeneous nature of this malignancy and the 
limited availability of informative tissue specimens from early stages of 
disease.
METHODOLOGY/PRINCIPLE FINDINGS: In order to gain an improved understanding of 
the molecular basis of melanoma progression, we have compared gene expression 
profiles from a series of melanoma cell lines representing discrete stages of 
malignant progression that recapitulate critical characteristics of the primary 
lesions from which they were derived. Here we describe the unsupervised 
hierarchical clustering of profiling data from melanoma cell lines and 
melanocytes. This clustering identifies two distinctive molecular subclasses of 
melanoma segregating aggressive metastatic tumor cell lines from less-aggressive 
primary tumor cell lines. Further analysis of expression signatures associated 
with melanoma progression using functional annotations categorized these 
transcripts into three classes of genes: 1) Upregulation of activators of cell 
cycle progression, DNA replication and repair (CDCA2, NCAPH, NCAPG, NCAPG2, PBK, 
NUSAP1, BIRC5, ESCO2, HELLS, MELK, GINS1, GINS4, RAD54L, TYMS, and DHFR), 2) 
Loss of genes associated with cellular adhesion and melanocyte differentiation 
(CDH3, CDH1, c-KIT, PAX3, CITED1/MSG-1, TYR, MELANA, MC1R, and OCA2), 3) 
Upregulation of genes associated with resistance to apoptosis (BIRC5/survivin). 
While these broad classes of transcripts have previously been implicated in the 
progression of melanoma and other malignancies, the specific genes identified 
within each class of transcripts are novel. In addition, the transcription 
factor NF-KB was specifically identified as being a potential "master regulator" 
of melanoma invasion since NF-KB binding sites were identified as consistent 
consensus sequences within promoters of progression-associated genes.
CONCLUSIONS/SIGNIFICANCE: We conclude that tumor cell lines are a valuable 
resource for the early identification of gene signatures associated with 
malignant progression in tumors with significant heterogeneity like melanoma. We 
further conclude that the development of novel data reduction algorithms for 
analysis of microarray studies is critical to allow for optimized mining of 
important, clinically-relevant datasets. It is expected that subsequent 
validation studies in primary human tissues using such an approach will lead to 
more rapid translation of such studies to the identification of novel tumor 
biomarkers and therapeutic targets.