Multi-platform whole-genome microarray analyses refine the epigenetic signature of breast cancer metastasis with gene expression and copy number.

<h4>Background</h4>We 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...

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Autores principales:	Joseph Andrews, Wendy Kennette, Jenna Pilon, Alexandra Hodgson, Alan B Tuck, Ann F Chambers, David I Rodenhiser
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2010
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/083ed21a7a92410faf37d5733e161a66
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spelling	oai:doaj.org-article:083ed21a7a92410faf37d5733e161a662021-11-25T06:26:45ZMulti-platform whole-genome microarray analyses refine the epigenetic signature of breast cancer metastasis with gene expression and copy number.1932-620310.1371/journal.pone.0008665https://doaj.org/article/083ed21a7a92410faf37d5733e161a662010-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20084286/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>We 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.<h4>Methodology/principal findings</h4>We 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.<h4>Conclusions/significance</h4>Our approach allows more precisely profiling of functionally relevant epigenetic signatures that are associated with cancer progression and metastasis.Joseph AndrewsWendy KennetteJenna PilonAlexandra HodgsonAlan B TuckAnn F ChambersDavid I RodenhiserPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 5, Iss 1, p e8665 (2010)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Joseph Andrews Wendy Kennette Jenna Pilon Alexandra Hodgson Alan B Tuck Ann F Chambers David I Rodenhiser Multi-platform whole-genome microarray analyses refine the epigenetic signature of breast cancer metastasis with gene expression and copy number.
description	<h4>Background</h4>We 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.<h4>Methodology/principal findings</h4>We 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.<h4>Conclusions/significance</h4>Our approach allows more precisely profiling of functionally relevant epigenetic signatures that are associated with cancer progression and metastasis.
format	article
author	Joseph Andrews Wendy Kennette Jenna Pilon Alexandra Hodgson Alan B Tuck Ann F Chambers David I Rodenhiser
author_facet	Joseph Andrews Wendy Kennette Jenna Pilon Alexandra Hodgson Alan B Tuck Ann F Chambers David I Rodenhiser
author_sort	Joseph Andrews
title	Multi-platform whole-genome microarray analyses refine the epigenetic signature of breast cancer metastasis with gene expression and copy number.
title_short	Multi-platform whole-genome microarray analyses refine the epigenetic signature of breast cancer metastasis with gene expression and copy number.
title_full	Multi-platform whole-genome microarray analyses refine the epigenetic signature of breast cancer metastasis with gene expression and copy number.
title_fullStr	Multi-platform whole-genome microarray analyses refine the epigenetic signature of breast cancer metastasis with gene expression and copy number.
title_full_unstemmed	Multi-platform whole-genome microarray analyses refine the epigenetic signature of breast cancer metastasis with gene expression and copy number.
title_sort	multi-platform whole-genome microarray analyses refine the epigenetic signature of breast cancer metastasis with gene expression and copy number.
publisher	Public Library of Science (PLoS)
publishDate	2010
url	https://doaj.org/article/083ed21a7a92410faf37d5733e161a66
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Multi-platform whole-genome microarray analyses refine the epigenetic signature of breast cancer metastasis with gene expression and copy number.

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