A strategy for full interrogation of prognostic gene expression patterns: exploring the biology of diffuse large B cell lymphoma.

<h4>Background</h4>Gene expression profiling yields quantitative data on gene expression used to create prognostic models that accurately predict patient outcome in diffuse large B cell lymphoma (DLBCL). Often, data are analyzed with genes classified by whether they fall above or below t...

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Autores principales:	Lisa M Rimsza, Joseph M Unger, Margaret E Tome, Michael L Leblanc
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2011
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/147ec832f92b4ce991f6dc0ec2559736
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spelling	oai:doaj.org-article:147ec832f92b4ce991f6dc0ec25597362021-11-18T06:48:41ZA strategy for full interrogation of prognostic gene expression patterns: exploring the biology of diffuse large B cell lymphoma.1932-620310.1371/journal.pone.0022267https://doaj.org/article/147ec832f92b4ce991f6dc0ec25597362011-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21829609/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>Gene expression profiling yields quantitative data on gene expression used to create prognostic models that accurately predict patient outcome in diffuse large B cell lymphoma (DLBCL). Often, data are analyzed with genes classified by whether they fall above or below the median expression level. We sought to determine whether examining multiple cut-points might be a more powerful technique to investigate the association of gene expression with outcome.<h4>Methodology/principal findings</h4>We explored gene expression profiling data using variable cut-point analysis for 36 genes with reported prognostic value in DLBCL. We plotted two-group survival logrank test statistics against corresponding cut-points of the gene expression levels and smooth estimates of the hazard ratio of death versus gene expression levels. To facilitate comparisons we also standardized the expression of each of the genes by the fraction of patients that would be identified by any cut-point. A multiple comparison adjusted permutation p-value identified 3 different patterns of significance: 1) genes with significant cut-point points below the median, whose loss is associated with poor outcome (e.g. HLA-DR); 2) genes with significant cut-points above the median, whose over-expression is associated with poor outcome (e.g. CCND2); and 3) genes with significant cut-points on either side of the median, (e.g. extracellular molecules such as FN1).<h4>Conclusions/significance</h4>Variable cut-point analysis with permutation p-value calculation can be used to identify significant genes that would not otherwise be identified with median cut-points and may suggest biological patterns of gene effects.Lisa M RimszaJoseph M UngerMargaret E TomeMichael L LeblancPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 6, Iss 8, p e22267 (2011)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Lisa M Rimsza Joseph M Unger Margaret E Tome Michael L Leblanc A strategy for full interrogation of prognostic gene expression patterns: exploring the biology of diffuse large B cell lymphoma.
description	<h4>Background</h4>Gene expression profiling yields quantitative data on gene expression used to create prognostic models that accurately predict patient outcome in diffuse large B cell lymphoma (DLBCL). Often, data are analyzed with genes classified by whether they fall above or below the median expression level. We sought to determine whether examining multiple cut-points might be a more powerful technique to investigate the association of gene expression with outcome.<h4>Methodology/principal findings</h4>We explored gene expression profiling data using variable cut-point analysis for 36 genes with reported prognostic value in DLBCL. We plotted two-group survival logrank test statistics against corresponding cut-points of the gene expression levels and smooth estimates of the hazard ratio of death versus gene expression levels. To facilitate comparisons we also standardized the expression of each of the genes by the fraction of patients that would be identified by any cut-point. A multiple comparison adjusted permutation p-value identified 3 different patterns of significance: 1) genes with significant cut-point points below the median, whose loss is associated with poor outcome (e.g. HLA-DR); 2) genes with significant cut-points above the median, whose over-expression is associated with poor outcome (e.g. CCND2); and 3) genes with significant cut-points on either side of the median, (e.g. extracellular molecules such as FN1).<h4>Conclusions/significance</h4>Variable cut-point analysis with permutation p-value calculation can be used to identify significant genes that would not otherwise be identified with median cut-points and may suggest biological patterns of gene effects.
format	article
author	Lisa M Rimsza Joseph M Unger Margaret E Tome Michael L Leblanc
author_facet	Lisa M Rimsza Joseph M Unger Margaret E Tome Michael L Leblanc
author_sort	Lisa M Rimsza
title	A strategy for full interrogation of prognostic gene expression patterns: exploring the biology of diffuse large B cell lymphoma.
title_short	A strategy for full interrogation of prognostic gene expression patterns: exploring the biology of diffuse large B cell lymphoma.
title_full	A strategy for full interrogation of prognostic gene expression patterns: exploring the biology of diffuse large B cell lymphoma.
title_fullStr	A strategy for full interrogation of prognostic gene expression patterns: exploring the biology of diffuse large B cell lymphoma.
title_full_unstemmed	A strategy for full interrogation of prognostic gene expression patterns: exploring the biology of diffuse large B cell lymphoma.
title_sort	strategy for full interrogation of prognostic gene expression patterns: exploring the biology of diffuse large b cell lymphoma.
publisher	Public Library of Science (PLoS)
publishDate	2011
url	https://doaj.org/article/147ec832f92b4ce991f6dc0ec2559736
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A strategy for full interrogation of prognostic gene expression patterns: exploring the biology of diffuse large B cell lymphoma.

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