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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: Marzese DM

PROVIDER: S-ECPF-GEOD-44660 | biostudies-other | 2014 Jan

REPOSITORIES: biostudies-other

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Project description:BackgroundIt is known from recent studies that more than 90% of human multi-exon genes are subject to Alternative Splicing (AS), a key molecular mechanism in which multiple transcripts may be generated from a single gene. It is widely recognized that a breakdown in AS mechanisms plays an important role in cellular differentiation and pathologies. Polymerase Chain Reactions, microarrays and sequencing technologies have been applied to the study of transcript diversity arising from alternative expression. Last generation Affymetrix GeneChip Human Exon 1.0 ST Arrays offer a more detailed view of the gene expression profile providing information on the AS patterns. The exon array technology, with more than five million data points, can detect approximately one million exons, and it allows performing analyses at both gene and exon level. In this paper we describe BEAT, an integrated user-friendly bioinformatics framework to store, analyze and visualize exon arrays datasets. It combines a data warehouse approach with some rigorous statistical methods for assessing the AS of genes involved in diseases. Meta statistics are proposed as a novel approach to explore the analysis results. BEAT is available at http://beat.ba.itb.cnr.it.ResultsBEAT is a web tool which allows uploading and analyzing exon array datasets using standard statistical methods and an easy-to-use graphical web front-end. BEAT has been tested on a dataset with 173 samples and tuned using new datasets of exon array experiments from 28 colorectal cancer and 26 renal cell cancer samples produced at the Medical Genetics Unit of IRCCS Casa Sollievo della Sofferenza.To highlight all possible AS events, alternative names, accession Ids, Gene Ontology terms and biochemical pathways annotations are integrated with exon and gene level expression plots. The user can customize the results choosing custom thresholds for the statistical parameters and exploiting the available clinical data of the samples for a multivariate AS analysis.ConclusionsDespite exon array chips being widely used for transcriptomics studies, there is a lack of analysis tools offering advanced statistical features and requiring no programming knowledge. BEAT provides a user-friendly platform for a comprehensive study of AS events in human diseases, displaying the analysis results with easily interpretable and interactive tables and graphics.

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Affymetrix expression array data for melanoma progression to the brain

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