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A gene expression signature associated with survival in metastatic melanoma.

ABSTRACT: BACKGROUND: Current clinical and histopathological criteria used to define the prognosis of melanoma patients are inadequate for accurate prediction of clinical outcome. We investigated whether genome screening by means of high-throughput gene microarray might provide clinically useful information on patient survival. METHODS: Forty-three tumor tissues from 38 patients with stage III and stage IV melanoma were profiled with a 17,500 element cDNA microarray. Expression data were analyzed using significance analysis of microarrays (SAM) to identify genes associated with patient survival, and supervised principal components (SPC) to determine survival prediction. RESULTS: SAM analysis revealed a set of 80 probes, corresponding to 70 genes, associated with survival, i.e. 45 probes characterizing longer and 35 shorter survival times, respectively. These transcripts were included in a survival prediction model designed using SPC and cross-validation which allowed identifying 30 predicting probes out of the 80 associated with survival. CONCLUSION: The longer-survival group of genes included those expressed in immune cells, both innate and acquired, confirming the interplay between immunological mechanisms and the natural history of melanoma. Genes linked to immune cells were totally lacking in the poor-survival group, which was instead associated with a number of genes related to highly proliferative and invasive tumor cells.

SUBMITTER: Mandruzzato S

PROVIDER: S-EPMC1697826 | biostudies-literature | 2006

REPOSITORIES: biostudies-literature

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A gene expression signature associated with survival in metastatic melanoma.

Mandruzzato Susanna S Callegaro Andrea A Turcatel Gianluca G Francescato Samuela S Montesco Maria C MC Chiarion-Sileni Vanna V Mocellin Simone S Rossi Carlo R CR Bicciato Silvio S Wang Ena E Marincola Francesco M FM Zanovello Paola P

Journal of translational medicine 20061127

<h4>Background</h4>Current clinical and histopathological criteria used to define the prognosis of melanoma patients are inadequate for accurate prediction of clinical outcome. We investigated whether genome screening by means of high-throughput gene microarray might provide clinically useful information on patient survival.<h4>Methods</h4>Forty-three tumor tissues from 38 patients with stage III and stage IV melanoma were profiled with a 17,500 element cDNA microarray. Expression data were anal ...[more]

PMID: 17129373

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Project description:Background:Melanoma is defined as a highly mutational heterogeneous disease containing numerous alternations of the molecule. However, due to the phenotypically and genetically heterogeneity of malignant melanoma, conventional clinical characteristics remain restricted or limited in the ability to accurately predict individual outcomes and survival. This study aimed to establish an accurate gene expression signature to predict melanoma prognosis. Methods:In this study, we established an RNA sequencing-based 12-gene signature data of melanoma patients obtained from 2 independent databases: the Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. We evaluated the quality of each gene to predict survival conditions in each database by employing univariate and multivariate regression models. A prognostic risk score based on a prognostic signature was determined. This prognostic gene signature further classified patients into low-risk and high-risk groups. Results:Based on a prognostic signature, a prognostic risk score was determined. This prognostic gene signature further divided the patients into low-risk and high-risk groups. In the chemotherapy and radiotherapy groups of the TCGA cohort and V-raf murine sarcoma viral oncogene homolog B1 (BRAF) expression group in the GEO cohort, patients in the low-risk group had a longer survival duration compared to patients in the high-risk group. Nevertheless, the immunotherapy group in the TCGA database and neuroblastoma RAS viral oncogene homolog (NRAS) expression group in the GEO database had no significant differences in statistics. Moreover, this gene signature was associated with patient prognosis regardless of whether the Breslow depth was greater than or less than 3.75 mm. Stratified gene set enrichment analysis (GSEA) revealed that certain immune-related pathways, such as the T-cell signaling pathway, chemokine signaling pathway, and primary immunodeficiency, were significantly enriched in the low-risk group of both TCGA and GEO cohorts. This information implied the immune-related properties of the 12-gene signature. Conclusions:Our study emphasizes the significance of the gene expression signature in that it may be an indispensable prognostic predictor in melanoma and has great potential for application in personalized treatment.

Project description:BackgroundDespite the extensive research approaches applied to characterise malignant melanoma, no specific molecular markers are available that are clearly related to the progression of this disease. In this study, our aims were to define a gene expression signature associated with the clinical outcome of melanoma patients and to provide an integrative interpretation of the gene expression -, copy number alterations -, and promoter methylation patterns that contribute to clinically relevant molecular functional alterations.MethodsGene expression profiles were determined using the Affymetrix U133 Plus2.0 array. The NimbleGen Human CGH Whole-Genome Tiling array was used to define CNAs, and the Illumina GoldenGate Methylation platform was applied to characterise the methylation patterns of overlapping genes.ResultsWE IDENTIFIED TWO SUBCLASSES OF PRIMARY MELANOMA: one representing patients with better prognoses and the other being characteristic of patients with unfavourable outcomes. We assigned 1,080 genes as being significantly correlated with ulceration, 987 genes were downregulated and significantly enriched in the p53, Nf-kappaB, and WNT/beta-catenin pathways. Through integrated genome analysis, we defined 150 downregulated genes whose expression correlated with copy number losses in ulcerated samples. These genes were significantly enriched on chromosome 6q and 10q, which contained a total of 36 genes. Ten of these genes were downregulated and involved in cell-cell and cell-matrix adhesion or apoptosis. The expression and methylation patterns of additional genes exhibited an inverse correlation, suggesting that transcriptional silencing of these genes is driven by epigenetic events.ConclusionUsing an integrative genomic approach, we were able to identify functionally relevant molecular hotspots characterised by copy number losses and promoter hypermethylation in distinct molecular subtypes of melanoma that contribute to specific transcriptomic silencing and might indicate a poor clinical outcome of melanoma.

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.

Dataset Information

A gene expression signature associated with survival in metastatic melanoma.

Publications

A gene expression signature associated with survival in metastatic melanoma.

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