Enhanced meta-analysis highlights genes involved in metastasis from several microarray datasets

M. Pierre, Benoît De Hertogh, Bertrand De Meulder, E. Bareke, S. Depiereux, C. Michiels, E. Depiereux

Résultats de recherche: Contribution à un journal/une revueArticle

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Résumé

Metastasis is the final stage of cancer and is still associated with high mortality despite breakthroughs in recent years. Hypoxia at the center of the primary tumor is a major cause of metastasis. Here, we present a new meta-analysis-based methodology to pick out genes involved in one or two biological processes from several microarray datasets using a statistic that avoids the definition of an arbitrary threshold, providing statistically-significant results. Applied to metastasis and hypoxia datasets, this methodology was able to select genes already known to be involved in these phenomena as well as new candidates for further analyses. 165 genes of interest were selected, many of which were already known to be involved in cancer, metastasis and/ or hypoxia. Moreover, some could be classified into 42 pathways, including 12 cancer pathways and 5 proliferation and cell motility pathways. Negative tests performed with random genes failed to provide such results. In additional independent validations, expression profiles were generated for the 165 genes of interest from two other datasets with MDA-MB-231, MCF-7 and L3.6pl cells and the previous results were confirmed in most cases. © 2011 Pierre M, et al.
langue originaleAnglais
Pages (de - à)36-43
Nombre de pages8
journalJournal of Proteomics and Bioinformatics
Volume4
Numéro de publication2
Les DOIs
étatPublié - 2011

Empreinte digitale

Microarrays
Meta-Analysis
Genes
Neoplasm Metastasis
Neoplasms
Biological Phenomena
MCF-7 Cells
Cell Movement
Tumors
Datasets
Statistics
Mortality
Hypoxia

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year = "2011",
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Enhanced meta-analysis highlights genes involved in metastasis from several microarray datasets. / Pierre, M.; De Hertogh, Benoît; De Meulder, Bertrand; Bareke, E.; Depiereux, S.; Michiels, C.; Depiereux, E.

Dans: Journal of Proteomics and Bioinformatics, Vol 4, Numéro 2, 2011, p. 36-43.

Résultats de recherche: Contribution à un journal/une revueArticle

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T1 - Enhanced meta-analysis highlights genes involved in metastasis from several microarray datasets

AU - Pierre, M.

AU - De Hertogh, Benoît

AU - De Meulder, Bertrand

AU - Bareke, E.

AU - Depiereux, S.

AU - Michiels, C.

AU - Depiereux, E.

N1 - Copyright 2011 Elsevier B.V., All rights reserved.

PY - 2011

Y1 - 2011

N2 - Metastasis is the final stage of cancer and is still associated with high mortality despite breakthroughs in recent years. Hypoxia at the center of the primary tumor is a major cause of metastasis. Here, we present a new meta-analysis-based methodology to pick out genes involved in one or two biological processes from several microarray datasets using a statistic that avoids the definition of an arbitrary threshold, providing statistically-significant results. Applied to metastasis and hypoxia datasets, this methodology was able to select genes already known to be involved in these phenomena as well as new candidates for further analyses. 165 genes of interest were selected, many of which were already known to be involved in cancer, metastasis and/ or hypoxia. Moreover, some could be classified into 42 pathways, including 12 cancer pathways and 5 proliferation and cell motility pathways. Negative tests performed with random genes failed to provide such results. In additional independent validations, expression profiles were generated for the 165 genes of interest from two other datasets with MDA-MB-231, MCF-7 and L3.6pl cells and the previous results were confirmed in most cases. © 2011 Pierre M, et al.

AB - Metastasis is the final stage of cancer and is still associated with high mortality despite breakthroughs in recent years. Hypoxia at the center of the primary tumor is a major cause of metastasis. Here, we present a new meta-analysis-based methodology to pick out genes involved in one or two biological processes from several microarray datasets using a statistic that avoids the definition of an arbitrary threshold, providing statistically-significant results. Applied to metastasis and hypoxia datasets, this methodology was able to select genes already known to be involved in these phenomena as well as new candidates for further analyses. 165 genes of interest were selected, many of which were already known to be involved in cancer, metastasis and/ or hypoxia. Moreover, some could be classified into 42 pathways, including 12 cancer pathways and 5 proliferation and cell motility pathways. Negative tests performed with random genes failed to provide such results. In additional independent validations, expression profiles were generated for the 165 genes of interest from two other datasets with MDA-MB-231, MCF-7 and L3.6pl cells and the previous results were confirmed in most cases. © 2011 Pierre M, et al.

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