Unknown,Transcriptomics,Genomics,Proteomics

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Affymetrix expression array data for melanoma progression to the brain


ABSTRACT: Melanoma is one of the most aggressive and treatment-resistant cancers. It represents the most life-threatening neoplasm of the skin, and its incidence has been increasing for the last three decades. Melanoma evolves from the local transformation of melanocytes to primary tumors, which can metastasize to multiple organs. Brain metastases represent one of the most significant causes of death in cutaneous melanoma patients. Despite aggressive multi-modality threapy, patients with melanoma brain metastasis have a median survival of less than a year, with a majority of these patients dying as a result of their intracranial disease. To identify alterations in gene expression related to brain metastasis, we used Affymetrix expression arrays to assess differentially expressed genes in melanocytes, lymph node metastases, and brain metastases. Total RNA from twenty-two specimens representing normal melanocytes (n=3), melanoma lymph node metastasis (n=12), and melanoma brain metastasis (n=7) was extracted and analyzed by Affymetrix expression arrays. Melanocytes specimens were used as control samples. Melanocytes were acquired from Invitrogen (LifeTechnologies). Metastatic melanoma specimens were taken from different patients, established as cell lines in the John Wayne Cancer Institute. Early passages (less than 6) were used to perform expression analysis.

ORGANISM(S): Homo sapiens

SUBMITTER: Dave Hoon 

PROVIDER: E-GEOD-44660 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications


Melanoma brain metastasis (MBM) represents a frequent complication of cutaneous melanoma. Despite aggressive multi-modality therapy, patients with MBM often have a survival rate of <1 year. Alteration in DNA methylation is a major hallmark of tumor progression and metastasis; however, it remains largely unexplored in MBM. In this study, we generated a comprehensive DNA methylation landscape through the use of genome-wide copy number, DNA methylation and gene expression data integrative analysis  ...[more]

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