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Gene expression profiling of brain metastatic melanoma cell lines

ABSTRACT: Cerebral metastases occur in a majority of metastatic melanoma patients and are a major cause of mortality. Despite this, there is a poor understanding of the molecules/pathways that lead to the brain-metastatic phenotype. Studies designed to address this deficiency and test novel therapeutic approaches have until recently been slowed by an absence of preclinical models of spontaneous CNS metastatic melanoma disease. To address this, we isolated two variants of the human melanoma cell line WM239 (named 131/4-5B1 and 131/4-5B2) which can metastasize spontaneously to brain parenchyma from an orthotopic primary transplant. We have performed gene expression profiling on both brain metastatic cell lines (131/4-5B1 and 131/4-5B2) and compared to the poorly metastatic parental cell line WM239A and a derived highly metastatic variant 113/6-4L in order to examine the mechanisms that influence the progression of malignant melanoma to a brain-metastatic phenotype. Two-condition experiment, brain metastatic cell lines (131/4-5B1 and 131/4-5B2) and compared to the poorly metastatic parental cell line WM239A and a derived highly metastatic variant 113/6-4L. Biological replicates: 4 independently grown and harvested cell line passages. Two technical replicate per condition (including dye swap).

ORGANISM(S): Homo sapiens

SUBMITTER: Cruz-Muñoz W

PROVIDER: S-ECPF-GEOD-23601 | biostudies-other | 2012 Oct

REPOSITORIES: biostudies-other

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Project description:Melanoma can progress rapidly from a slow-growing surgically curable lesion to aggressive metastatic disease, with high mortality and poor response to current therapies. The mechanisms underlying melanoma progression and resistance to therapeutic agents are not well understood. There are few treatment options for melanoma once it has metastasized, and new biomarkers that aid diagnosis, predict clinical outcome, and suggest new therapies are required. This aim of this study was to invesigate the molecular basis of melanoma biology and heterogeneity by defining genomic characteristics that correlated with tumour phenotype in a novel panel of 25 cell lines derived largely from New Zealand patients with metastatic melanoma. The goals of this study were to (i) stratify melanoma cell lines by using global gene expression profiling ; (ii) correlate gene expression profiles with invasive potential; and (iii) identify new prognostic markers and therapeutic targets that might aid clinical cancer diagnosis and management. Two-colour spotted oligonucleotide microarrays were used to measure global gene expression in metastatic melanoma cell lines against a common universal reference. Biological replication was achieved by performing replicate arrays on a subset of randomly selected cell lines, in which the replicate total RNA samples were isolated from different vials of cells at different passage numbers, grown by different researchers, and often in different laboratories. Further, NZM01 and NZM02 were derived from different tumours from the same patient at different surgeries, and NZM07.2 and 07.4 were derived from the NZM07 cell line. The array hybridisations were peformed in three batches. Technical replication was achieved by using intra- and inter-batch replicates with different RNA samples from 6/25 of the cell lines: NZM04, 2 x batch 1, 1 x batch 2; NZM22, 2 x batch 1; NZM40, 1 x batch 1, 1 x batch 2; NZM06, 1 x batch 1, 1 x batch 3; NZM09, 1 x batch 1, 1 x batch 2; NZM15, 1 x batch 2, 1 x batch 3.

Project description:BackgroundGene 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 findingsIn 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/significanceWe 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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Gene expression profiling of brain metastatic melanoma cell lines

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