ArticlePloS one2010
Multi-platform whole-genome microarray analyses refine the epigenetic signature of breast cancer metastasis with gene expression and copy number.
Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed, 58 citations in OpenAlex.
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- The Lq- NORM LEARNING FOR ULTRAHIGH-DIMENSIONAL SURVIVAL DATA: AN INTEGRATIVE FRAMEWORK.Statistica Sinica · 2020Article
- Detection and analysis of stable and flexible genes towards a genome signature framework in cancer.Bioinformation · 2019Article
- Epigenetic regulation of gene expression in cancer: techniques, resources and analysis.Briefings in functional genomics · 2018Article
- Integrating genetics and epigenetics in breast cancer: biological insights, experimental, computational methods and therapeutic potential.BMC systems biology · 2015Review
- Combining multidimensional genomic measurements for predicting cancer prognosis: observations from TCGA.Briefings in bioinformatics · 2015Article
- CHST11 gene expression and DNA methylation in breast cancer.International journal of oncology · 2015Article
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- Potential Role of Selenoenzymes and Antioxidant Metabolism in relation to Autism Etiology and Pathology.Autism research and treatment · 2014Review
- Integrated analysis of genome-wide copy number alterations and gene expression in microsatellite stable, CpG island methylator phenotype-negative colon cancer.Genes, chromosomes & cancer · 2013Article
- The molecular genomics of metastatic brain tumours.OA molecular oncology · 2013Article
- Cancer gene prioritization by integrative analysis of mRNA expression and DNA copy number data: a comparative review.Briefings in bioinformatics · 2013Review
- Article
- Strategies for the discovery and development of therapies for metastatic breast cancer.Nature reviews. Drug discovery · 2012Review
- Amplifications of NCOA3 gene in colorectal cancers in a Chinese population.World journal of gastroenterology · 2012Article
- Estimation of a non-parametric variable importance measure of a continuous exposure.Electronic journal of statistics · 2012Article
- Application of microarray in breast cancer: An overview.Journal of pharmacy & bioallied sciences · 2012Article
- DNA methylation signatures for breast cancer classification and prognosis.Genome medicine · 2012Review
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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/SIGNIFICANCE: Our approach allows more precisely profiling of functionally relevant epigenetic signatures that are associated with cancer progression and metastasis.
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