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Chromosomal patterns of gene expression from microarray data: methodology, validation and clinical relevance in gliomas
BACKGROUND: Expression microarrays represent a powerful technique for the simultaneous investigation of thousands of genes. The evidence that genes are not randomly distributed in the genome and that their coordinated expression depends on their position on chromosomes has highlighted the need for m...
Autores principales: | , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2006
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1698583/ https://www.ncbi.nlm.nih.gov/pubmed/17140431 http://dx.doi.org/10.1186/1471-2105-7-526 |
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author | Turkheimer, Federico E Roncaroli, Federico Hennuy, Benoit Herens, Christian Nguyen, Minh Martin, Didier Evrard, Annick Bours, Vincent Boniver, Jacques Deprez, Manuel |
author_facet | Turkheimer, Federico E Roncaroli, Federico Hennuy, Benoit Herens, Christian Nguyen, Minh Martin, Didier Evrard, Annick Bours, Vincent Boniver, Jacques Deprez, Manuel |
author_sort | Turkheimer, Federico E |
collection | PubMed |
description | BACKGROUND: Expression microarrays represent a powerful technique for the simultaneous investigation of thousands of genes. The evidence that genes are not randomly distributed in the genome and that their coordinated expression depends on their position on chromosomes has highlighted the need for mathematical approaches to exploit this dependency for the analysis of expression data-sets. RESULTS: We have devised a novel mathematical technique (CHROMOWAVE) based on the Haar wavelet transform and applied it to a dataset obtained with the Affymetrix(® )HG-U133_Plus_2 array in 27 gliomas. CHROMOWAVE generated multi-chromosomal pattern featuring low expression in chromosomes 1p, 4, 9q, 13, 18, and 19q. This pattern was not only statistically robust but also clinically relevant as it was predictive of favourable outcome. This finding was replicated on a data-set independently acquired by another laboratory. FISH analysis indicated that monosomy 1p and 19q was a frequent feature of tumours displaying the CHROMOWAVE pattern but that allelic loss on chromosomes 4, 9q, 13 and 18 was much less common. CONCLUSION: The ability to detect expression changes of spatially related genes and to map their position on chromosomes makes CHROMOWAVE a valuable screening method for the identification and display of regional gene expression changes of clinical relevance. In this study, FISH data showed that monosomy was frequently associated with diffuse low gene expression on chromosome 1p and 19q but not on chromosomes 4, 9q, 13 and 18. Comparative genomic hybridisation, allelic polymorphism analysis and methylation studies are in progress in order to identify the various mechanisms involved in this multi-chromosomal expression pattern. |
format | Text |
id | pubmed-1698583 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-16985832006-12-19 Chromosomal patterns of gene expression from microarray data: methodology, validation and clinical relevance in gliomas Turkheimer, Federico E Roncaroli, Federico Hennuy, Benoit Herens, Christian Nguyen, Minh Martin, Didier Evrard, Annick Bours, Vincent Boniver, Jacques Deprez, Manuel BMC Bioinformatics Research Article BACKGROUND: Expression microarrays represent a powerful technique for the simultaneous investigation of thousands of genes. The evidence that genes are not randomly distributed in the genome and that their coordinated expression depends on their position on chromosomes has highlighted the need for mathematical approaches to exploit this dependency for the analysis of expression data-sets. RESULTS: We have devised a novel mathematical technique (CHROMOWAVE) based on the Haar wavelet transform and applied it to a dataset obtained with the Affymetrix(® )HG-U133_Plus_2 array in 27 gliomas. CHROMOWAVE generated multi-chromosomal pattern featuring low expression in chromosomes 1p, 4, 9q, 13, 18, and 19q. This pattern was not only statistically robust but also clinically relevant as it was predictive of favourable outcome. This finding was replicated on a data-set independently acquired by another laboratory. FISH analysis indicated that monosomy 1p and 19q was a frequent feature of tumours displaying the CHROMOWAVE pattern but that allelic loss on chromosomes 4, 9q, 13 and 18 was much less common. CONCLUSION: The ability to detect expression changes of spatially related genes and to map their position on chromosomes makes CHROMOWAVE a valuable screening method for the identification and display of regional gene expression changes of clinical relevance. In this study, FISH data showed that monosomy was frequently associated with diffuse low gene expression on chromosome 1p and 19q but not on chromosomes 4, 9q, 13 and 18. Comparative genomic hybridisation, allelic polymorphism analysis and methylation studies are in progress in order to identify the various mechanisms involved in this multi-chromosomal expression pattern. BioMed Central 2006-12-01 /pmc/articles/PMC1698583/ /pubmed/17140431 http://dx.doi.org/10.1186/1471-2105-7-526 Text en Copyright © 2006 Turkheimer et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Turkheimer, Federico E Roncaroli, Federico Hennuy, Benoit Herens, Christian Nguyen, Minh Martin, Didier Evrard, Annick Bours, Vincent Boniver, Jacques Deprez, Manuel Chromosomal patterns of gene expression from microarray data: methodology, validation and clinical relevance in gliomas |
title | Chromosomal patterns of gene expression from microarray data: methodology, validation and clinical relevance in gliomas |
title_full | Chromosomal patterns of gene expression from microarray data: methodology, validation and clinical relevance in gliomas |
title_fullStr | Chromosomal patterns of gene expression from microarray data: methodology, validation and clinical relevance in gliomas |
title_full_unstemmed | Chromosomal patterns of gene expression from microarray data: methodology, validation and clinical relevance in gliomas |
title_short | Chromosomal patterns of gene expression from microarray data: methodology, validation and clinical relevance in gliomas |
title_sort | chromosomal patterns of gene expression from microarray data: methodology, validation and clinical relevance in gliomas |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1698583/ https://www.ncbi.nlm.nih.gov/pubmed/17140431 http://dx.doi.org/10.1186/1471-2105-7-526 |
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