Linked Life Data

17044051

Source:http://linkedlifedata.com/resource/pubmed/id/17044051

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2006-11-13
pubmed:abstractText
Chromosomal aneuploidy is commonly observed in neoplastic diseases and is an important prognostic marker. Here we examine how gene expression profiles reflect aneuploidy and whether these profiles can be used to detect changes in chromosome copy number. We developed two methods for detecting such changes in the gene expression profile of a single sample. The first method, fold-change analysis, relies on the availability of gene expression data from a large cohort of patients with the same disease. The expression profile of the sample is compared with that of the dataset. The second method, chromosomal relative expression analysis, is more general and requires the expression data from the tested sample only. We found that the relative expression values are stable among different chromosomes and exhibit little variation between different normal tissues. We exploited this novel finding to establish the set of reference values needed to detect changes in the copy number of chromosomes in a single sample on the basis of gene expression levels. We measured the accuracy of the performance of each method by applying them to two independent leukemia datasets. The second method was also applied to two solid tumor datasets. We conclude that chromosomal aneuploidy can be detected and predicted by analysis of gene expression profiles. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045-2257/suppmat.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
1045-2257
pubmed:author
pubmed:copyrightInfo
Copyright 2006 Wiley-Liss, Inc.
pubmed:issnType
Print
pubmed:volume
46
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
75-86
pubmed:dateRevised
2007-12-3
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Prediction of chromosomal aneuploidy from gene expression data.
pubmed:affiliation
Department of Pediatric Hemato-Oncology, The Sheba Cancer Research Center, Sheba Medical Center, Tel Hashomer, Israel.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural