Multi-Platform Whole-Genome Microarray Analyses Refine the Epigenetic Signature of Breast Cancer Metastasis with Gene Expression and Copy Number
| Autor: | Ann F. Chambers, David I. Rodenhiser, Alan B. Tuck, Joseph Andrews, Alexandra Hodgson, Jenna Pilon, Wendy Kennette |
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| Rok vydání: | 2010 |
| Předmět: |
Science
Breast Neoplasms Computational biology Biology Biochemistry Pediatrics Polymorphism Single Nucleotide Gene dosage Epigenesis Genetic Metastasis breast cancer Genetics and Genomics/Epigenetics Cell Line Tumor Pathology medicine Humans Epigenetics Copy-number variation Neoplasm Metastasis genome Genetics and Genomics/Cancer Genetics Gene Oligonucleotide Array Sequence Analysis Genetics Genome Multidisciplinary Reverse Transcriptase Polymerase Chain Reaction Microarray analysis techniques DNA Methylation medicine.disease Oncology Biochemistry/Bioinformatics Oncology/Breast Cancer DNA methylation gene expression Medicine Female microarray analysis DNA microarray Research Article |
| Zdroj: | PLoS ONE, Vol 5, Iss 1, p e8665 (2010) PLoS ONE Biochemistry Publications |
| ISSN: | 1932-6203 |
| DOI: | 10.1371/journal.pone.0008665 |
| Popis: | BackgroundWe have previously identified genome-wide DNA methylation changes in a cell line model of breast cancer metastasis. These complex epigenetic changes that we observed, along with concurrent karyotype analyses, have led us to hypothesize that complex genomic alterations in cancer cells (deletions, translocations and ploidy) are superimposed over promoter-specific methylation events that are responsible for gene-specific expression changes observed in breast cancer metastasis.Methodology/principal findingsWe undertook simultaneous high-resolution, whole-genome analyses of MDA-MB-468GFP and MDA-MB-468GFP-LN human breast cancer cell lines (an isogenic, paired lymphatic metastasis cell line model) using Affymetrix gene expression (U133), promoter (1.0R), and SNP/CNV (SNP 6.0) microarray platforms to correlate data from gene expression, epigenetic (DNA methylation), and combination copy number variant/single nucleotide polymorphism microarrays. Using Partek Software and Ingenuity Pathway Analysis we integrated datasets from these three platforms and detected multiple hypomethylation and hypermethylation events. Many of these epigenetic alterations correlated with gene expression changes. In addition, gene dosage events correlated with the karyotypic differences observed between the cell lines and were reflected in specific promoter methylation patterns. Gene subsets were identified that correlated hyper (and hypo) methylation with the loss (or gain) of gene expression and in parallel, with gene dosage losses and gains, respectively. Individual gene targets from these subsets were also validated for their methylation, expression and copy number status, and susceptible gene pathways were identified that may indicate how selective advantage drives the processes of tumourigenesis and metastasis.Conclusions/significanceOur approach allows more precisely profiling of functionally relevant epigenetic signatures that are associated with cancer progression and metastasis. |
| Databáze: | OpenAIRE |
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