Cargando…

Molecular classification of selective oestrogen receptor modulators on the basis of gene expression profiles of breast cancer cells expressing oestrogen receptor α

The purpose of this study was to classify selective oestrogen receptor modulators based on gene expression profiles produced in breast cancer cells expressing either wtERα or mutant(351)ERα. In total, 54 microarray experiments were carried out by using a commercially available Atlas cDNA Expression...

Descripción completa

Detalles Bibliográficos
Autores principales: Levenson, A S, Kliakhandler, I L, Svoboda, K M, Pease, K M, Kaiser, S A, Ward, III, J E, Jordan, V C
Formato: Texto
Lenguaje:English
Publicado: Nature Publishing Group 2002
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2376139/
https://www.ncbi.nlm.nih.gov/pubmed/12177783
http://dx.doi.org/10.1038/sj.bjc.6600477
_version_ 1782154699264229376
author Levenson, A S
Kliakhandler, I L
Svoboda, K M
Pease, K M
Kaiser, S A
Ward, III, J E
Jordan, V C
author_facet Levenson, A S
Kliakhandler, I L
Svoboda, K M
Pease, K M
Kaiser, S A
Ward, III, J E
Jordan, V C
author_sort Levenson, A S
collection PubMed
description The purpose of this study was to classify selective oestrogen receptor modulators based on gene expression profiles produced in breast cancer cells expressing either wtERα or mutant(351)ERα. In total, 54 microarray experiments were carried out by using a commercially available Atlas cDNA Expression Arrays (Clontech), containing 588 cancer-related genes. Nine sets of data were generated for each cell line following 24 h of treatment: expression data were obtained for cells treated with vehicle EtOH (Control); with 10(−9) or 10(−8) M oestradiol; with 10(−6) M 4-hydroxytamoxifen; with 10(−6) M raloxifene; with 10(−6) M idoxifene, with 10(−6) M EM 652, with 10(−6) M GW 7604; with 5×10(−5) M resveratrol and with 10(−6) M ICI 182,780. We developed a new algorithm ‘Expression Signatures’ to classify compounds on the basis of differential gene expression profiles. We created dendrograms for each cell line, in which branches represent relationships between compounds. Additionally, clustering analysis was performed using different subsets of genes to assess the robustness of the analysis. In general, only small differences between gene expression profiles treated with compounds were observed with correlation coefficients ranged from 0.83 to 0.98. This observation may be explained by the use of the same cell context for treatments with compounds that essentially belong to the same class of drugs with oestrogen receptors related mechanisms. The most surprising observation was that ICI 182,780 clustered together with oestrodiol and raloxifene for cells expressing wtERα and clustered together with EM 652 for cells expressing mutant(351)ERα. These data provide a rationale for a more precise and elaborate study in which custom made oligonucleotide arrays can be used with comprehensive sets of genes known to have consensus and putative oestrogen response elements in their promoter regions. British Journal of Cancer (2002) 87, 449–456. doi:10.1038/sj.bjc.6600477 www.bjcancer.com © 2002 Cancer Research UK
format Text
id pubmed-2376139
institution National Center for Biotechnology Information
language English
publishDate 2002
publisher Nature Publishing Group
record_format MEDLINE/PubMed
spelling pubmed-23761392009-09-10 Molecular classification of selective oestrogen receptor modulators on the basis of gene expression profiles of breast cancer cells expressing oestrogen receptor α Levenson, A S Kliakhandler, I L Svoboda, K M Pease, K M Kaiser, S A Ward, III, J E Jordan, V C Br J Cancer Experimental Therapeutics The purpose of this study was to classify selective oestrogen receptor modulators based on gene expression profiles produced in breast cancer cells expressing either wtERα or mutant(351)ERα. In total, 54 microarray experiments were carried out by using a commercially available Atlas cDNA Expression Arrays (Clontech), containing 588 cancer-related genes. Nine sets of data were generated for each cell line following 24 h of treatment: expression data were obtained for cells treated with vehicle EtOH (Control); with 10(−9) or 10(−8) M oestradiol; with 10(−6) M 4-hydroxytamoxifen; with 10(−6) M raloxifene; with 10(−6) M idoxifene, with 10(−6) M EM 652, with 10(−6) M GW 7604; with 5×10(−5) M resveratrol and with 10(−6) M ICI 182,780. We developed a new algorithm ‘Expression Signatures’ to classify compounds on the basis of differential gene expression profiles. We created dendrograms for each cell line, in which branches represent relationships between compounds. Additionally, clustering analysis was performed using different subsets of genes to assess the robustness of the analysis. In general, only small differences between gene expression profiles treated with compounds were observed with correlation coefficients ranged from 0.83 to 0.98. This observation may be explained by the use of the same cell context for treatments with compounds that essentially belong to the same class of drugs with oestrogen receptors related mechanisms. The most surprising observation was that ICI 182,780 clustered together with oestrodiol and raloxifene for cells expressing wtERα and clustered together with EM 652 for cells expressing mutant(351)ERα. These data provide a rationale for a more precise and elaborate study in which custom made oligonucleotide arrays can be used with comprehensive sets of genes known to have consensus and putative oestrogen response elements in their promoter regions. British Journal of Cancer (2002) 87, 449–456. doi:10.1038/sj.bjc.6600477 www.bjcancer.com © 2002 Cancer Research UK Nature Publishing Group 2002-08-12 /pmc/articles/PMC2376139/ /pubmed/12177783 http://dx.doi.org/10.1038/sj.bjc.6600477 Text en Copyright © 2002 Cancer Research UK https://creativecommons.org/licenses/by/4.0/This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material.If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/.
spellingShingle Experimental Therapeutics
Levenson, A S
Kliakhandler, I L
Svoboda, K M
Pease, K M
Kaiser, S A
Ward, III, J E
Jordan, V C
Molecular classification of selective oestrogen receptor modulators on the basis of gene expression profiles of breast cancer cells expressing oestrogen receptor α
title Molecular classification of selective oestrogen receptor modulators on the basis of gene expression profiles of breast cancer cells expressing oestrogen receptor α
title_full Molecular classification of selective oestrogen receptor modulators on the basis of gene expression profiles of breast cancer cells expressing oestrogen receptor α
title_fullStr Molecular classification of selective oestrogen receptor modulators on the basis of gene expression profiles of breast cancer cells expressing oestrogen receptor α
title_full_unstemmed Molecular classification of selective oestrogen receptor modulators on the basis of gene expression profiles of breast cancer cells expressing oestrogen receptor α
title_short Molecular classification of selective oestrogen receptor modulators on the basis of gene expression profiles of breast cancer cells expressing oestrogen receptor α
title_sort molecular classification of selective oestrogen receptor modulators on the basis of gene expression profiles of breast cancer cells expressing oestrogen receptor α
topic Experimental Therapeutics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2376139/
https://www.ncbi.nlm.nih.gov/pubmed/12177783
http://dx.doi.org/10.1038/sj.bjc.6600477
work_keys_str_mv AT levensonas molecularclassificationofselectiveoestrogenreceptormodulatorsonthebasisofgeneexpressionprofilesofbreastcancercellsexpressingoestrogenreceptora
AT kliakhandleril molecularclassificationofselectiveoestrogenreceptormodulatorsonthebasisofgeneexpressionprofilesofbreastcancercellsexpressingoestrogenreceptora
AT svobodakm molecularclassificationofselectiveoestrogenreceptormodulatorsonthebasisofgeneexpressionprofilesofbreastcancercellsexpressingoestrogenreceptora
AT peasekm molecularclassificationofselectiveoestrogenreceptormodulatorsonthebasisofgeneexpressionprofilesofbreastcancercellsexpressingoestrogenreceptora
AT kaisersa molecularclassificationofselectiveoestrogenreceptormodulatorsonthebasisofgeneexpressionprofilesofbreastcancercellsexpressingoestrogenreceptora
AT wardiiije molecularclassificationofselectiveoestrogenreceptormodulatorsonthebasisofgeneexpressionprofilesofbreastcancercellsexpressingoestrogenreceptora
AT jordanvc molecularclassificationofselectiveoestrogenreceptormodulatorsonthebasisofgeneexpressionprofilesofbreastcancercellsexpressingoestrogenreceptora