Cross-study projections of genomic biomarkers: an evaluation in cancer genomics.

Human disease studies using DNA microarrays in both clinical/observational and experimental/controlled studies are having increasing impact on our understanding of the complexity of human diseases. A fundamental concept is the use of gene expression as a "common currency" that links the re...

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Autores principales:	Joseph E Lucas, Carlos M Carvalho, Julia Ling-Yu Chen, Jen-Tsan Chi, Mike West
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2009
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/2fa62723eb1d4f3fa41187d92a8d558f
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spelling	oai:doaj.org-article:2fa62723eb1d4f3fa41187d92a8d558f2021-11-25T06:17:14ZCross-study projections of genomic biomarkers: an evaluation in cancer genomics.1932-620310.1371/journal.pone.0004523https://doaj.org/article/2fa62723eb1d4f3fa41187d92a8d558f2009-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/19225561/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Human disease studies using DNA microarrays in both clinical/observational and experimental/controlled studies are having increasing impact on our understanding of the complexity of human diseases. A fundamental concept is the use of gene expression as a "common currency" that links the results of in vitro controlled experiments to in vivo observational human studies. Many studies--in cancer and other diseases--have shown promise in using in vitro cell manipulations to improve understanding of in vivo biology, but experiments often simply fail to reflect the enormous phenotypic variation seen in human diseases. We address this with a framework and methods to dissect, enhance and extend the in vivo utility of in vitro derived gene expression signatures. From an experimentally defined gene expression signature we use statistical factor analysis to generate multiple quantitative factors in human cancer gene expression data. These factors retain their relationship to the original, one-dimensional in vitro signature but better describe the diversity of in vivo biology. In a breast cancer analysis, we show that factors can reflect fundamentally different biological processes linked to molecular and clinical features of human cancers, and that in combination they can improve prediction of clinical outcomes.Joseph E LucasCarlos M CarvalhoJulia Ling-Yu ChenJen-Tsan ChiMike WestPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 4, Iss 2, p e4523 (2009)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Joseph E Lucas Carlos M Carvalho Julia Ling-Yu Chen Jen-Tsan Chi Mike West Cross-study projections of genomic biomarkers: an evaluation in cancer genomics.
description	Human disease studies using DNA microarrays in both clinical/observational and experimental/controlled studies are having increasing impact on our understanding of the complexity of human diseases. A fundamental concept is the use of gene expression as a "common currency" that links the results of in vitro controlled experiments to in vivo observational human studies. Many studies--in cancer and other diseases--have shown promise in using in vitro cell manipulations to improve understanding of in vivo biology, but experiments often simply fail to reflect the enormous phenotypic variation seen in human diseases. We address this with a framework and methods to dissect, enhance and extend the in vivo utility of in vitro derived gene expression signatures. From an experimentally defined gene expression signature we use statistical factor analysis to generate multiple quantitative factors in human cancer gene expression data. These factors retain their relationship to the original, one-dimensional in vitro signature but better describe the diversity of in vivo biology. In a breast cancer analysis, we show that factors can reflect fundamentally different biological processes linked to molecular and clinical features of human cancers, and that in combination they can improve prediction of clinical outcomes.
format	article
author	Joseph E Lucas Carlos M Carvalho Julia Ling-Yu Chen Jen-Tsan Chi Mike West
author_facet	Joseph E Lucas Carlos M Carvalho Julia Ling-Yu Chen Jen-Tsan Chi Mike West
author_sort	Joseph E Lucas
title	Cross-study projections of genomic biomarkers: an evaluation in cancer genomics.
title_short	Cross-study projections of genomic biomarkers: an evaluation in cancer genomics.
title_full	Cross-study projections of genomic biomarkers: an evaluation in cancer genomics.
title_fullStr	Cross-study projections of genomic biomarkers: an evaluation in cancer genomics.
title_full_unstemmed	Cross-study projections of genomic biomarkers: an evaluation in cancer genomics.
title_sort	cross-study projections of genomic biomarkers: an evaluation in cancer genomics.
publisher	Public Library of Science (PLoS)
publishDate	2009
url	https://doaj.org/article/2fa62723eb1d4f3fa41187d92a8d558f
work_keys_str_mv	AT josephelucas crossstudyprojectionsofgenomicbiomarkersanevaluationincancergenomics AT carlosmcarvalho crossstudyprojectionsofgenomicbiomarkersanevaluationincancergenomics AT julialingyuchen crossstudyprojectionsofgenomicbiomarkersanevaluationincancergenomics AT jentsanchi crossstudyprojectionsofgenomicbiomarkersanevaluationincancergenomics AT mikewest crossstudyprojectionsofgenomicbiomarkersanevaluationincancergenomics
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Cross-study projections of genomic biomarkers: an evaluation in cancer genomics.

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