Comprehensive Expression Profiling of Tumor Cell Lines Identifies Molecular Signatures of Melanoma Progression

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