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. 2007 Jul 4;2(7):e594.
doi: 10.1371/journal.pone.0000594.

Comprehensive expression profiling of tumor cell lines identifies molecular signatures of melanoma progression

Affiliations

Comprehensive expression profiling of tumor cell lines identifies molecular signatures of melanoma progression

Byungwoo Ryu et al. PLoS One. .

Abstract

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.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Evaluation of gene expression profiles from melanoma cells lines of varying stages of progression identifies a signature for aggressive melanomas.
A) Unsupervised hierarchical clustering of melanoma cells indicates the existence of two distinct groups of melanoma cells based on global gene expression patterns (Group 1: RGP2, RGP3, RGP1, VGP1, and VGP2; Group 2: VGP3, MM2, MM1, VGP4, and MM3). B) SAM plot sheet illustrating a signature for differentially expressed genes in aggressive melanomas. Gene expression profiles from the two groups of melanomas were compared (Group1 vs. Group 2) and a differentially expressed gene signature was identified by SAM. Red and green dots represent gene probesets upregulated and downregulated respectively in Group 2. C) The melanoma gene signature was visualized using Java TreeView. Genes over four-fold differentially expressed are indicated on the right side of the image. D) Validation of select differentially expressed genes by real-time RT-PCR. Three genes upregulated in aggressive melanomas (Group 2) were selected for analysis and their differential expression was verified. 3.0 µg of total RNA was subjected to cDNA synthesis reaction as described in the materials and methods. 1.0 µl of the final cDNA samples (100 µl) were used for real-time Q-PCR reaction. For the measurement of gene transcript level, standard curves were generated for each gene using known amount of PCR amplified product from the corresponding genes. Error bars are SD of three independent experiments.
Figure 2
Figure 2. Evaluation of differential gene expression from aggressive melanomas (Group 2) vs. primary human melanocytes identifies a signature characterized by loss of differentiation-associated genes.
A) Java TreeView analysis of melanoma cell lines and primary human melanocytes clusters two pools of human primary melanocytes (HPM1 and HPM2) with the Group 2 melanomas. B) SAM plot sheet illustrating a signature of down-regulated genes in group 2 melanomas compared to HPMs. Gene expression profiles of two pools of human primary melanocytes (HPM1 and HPM2) were compared to those of aggressive melanomas (Group 2) and a differentially expressed gene signature was identified by SAM. C) The melanoma gene signature was visualized using Java TreeView. Genes over five-fold downregulated are indicated on the right. D) Validation of differential expression for selected genes by semi-quantitative duplex RT-PCR. Four genes (CDH3, KIT, DPP4, SYK) downregulated in the aggressive melanoma cells (Group 2) were selected for analysis and their differential expression was verified.
Figure 3
Figure 3. Identification of an invasion-specific gene signature for melanoma.
A) The three-step data reduction algorithm used for identification of a melanoma invasion-specific signature. (see detailed description in Data Extraction and Statistical Analysis section of Methods). B) Relative expression levels of melanoma invasion-specific signature genes in all cells analyzed including human primary melanocytes (HPM1, HPM2). C) Validation of differential expression for selected genes by semi-quantitative duplex RT-PCR. Four genes (IL-8, IGFBP3, CXCL1, CXCL2) that are upregulated in invasive melanomas were selected and their differential expression was verified. D) Promoter analysis of selected genes from the melanoma invasion-specific signature identifies putative NF-κB binding cis elements. E) Immunofluorescence staining of NF-κB in invasive (WM902B) vs. non-invasive (WM1552C) melanoma cells demonstrates constitutive activation and nuclear trafficking of NF-κB in invasive melanomas.

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