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dc.contributor.author Lucas, JE
dc.contributor.author Kung, HN
dc.contributor.author Chi, JT
dc.coverage.spatial United States
dc.date.accessioned 2011-06-21T17:31:13Z
dc.date.issued 2010-09-02
dc.identifier http://www.ncbi.nlm.nih.gov/pubmed/20824128
dc.identifier.citation PLoS Comput Biol, 2010, 6 (9), pp. e1000920 - ?
dc.identifier.uri http://hdl.handle.net/10161/4453
dc.description.abstract Tumor microenvironmental stresses, such as hypoxia and lactic acidosis, play important roles in tumor progression. Although gene signatures reflecting the influence of these stresses are powerful approaches to link expression with phenotypes, they do not fully reflect the complexity of human cancers. Here, we describe the use of latent factor models to further dissect the stress gene signatures in a breast cancer expression dataset. The genes in these latent factors are coordinately expressed in tumors and depict distinct, interacting components of the biological processes. The genes in several latent factors are highly enriched in chromosomal locations. When these factors are analyzed in independent datasets with gene expression and array CGH data, the expression values of these factors are highly correlated with copy number alterations (CNAs) of the corresponding BAC clones in both the cell lines and tumors. Therefore, variation in the expression of these pathway-associated factors is at least partially caused by variation in gene dosage and CNAs among breast cancers. We have also found the expression of two latent factors without any chromosomal enrichment is highly associated with 12q CNA, likely an instance of "trans"-variations in which CNA leads to the variations in gene expression outside of the CNA region. In addition, we have found that factor 26 (1q CNA) is negatively correlated with HIF-1alpha protein and hypoxia pathways in breast tumors and cell lines. This agrees with, and for the first time links, known good prognosis associated with both a low hypoxia signature and the presence of CNA in this region. Taken together, these results suggest the possibility that tumor segmental aneuploidy makes significant contributions to variation in the lactic acidosis/hypoxia gene signatures in human cancers and demonstrate that latent factor analysis is a powerful means to uncover such a linkage.
dc.format.extent e1000920 - ?
dc.language eng
dc.language.iso en_US en_US
dc.relation.ispartof PLoS Comput Biol
dc.relation.isversionof 10.1371/journal.pcbi.1000920
dc.subject Acidosis, Lactic
dc.subject Aneuploidy
dc.subject Breast Neoplasms
dc.subject Cell Hypoxia
dc.subject Cell Line, Tumor
dc.subject Cluster Analysis
dc.subject Comparative Genomic Hybridization
dc.subject Computational Biology
dc.subject DNA Copy Number Variations
dc.subject Databases, Genetic
dc.subject Female
dc.subject Gene Dosage
dc.subject Gene Expression Profiling
dc.subject Gene Expression Regulation, Neoplastic
dc.subject Humans
dc.subject Models, Statistical
dc.subject Organ Specificity
dc.subject RNA, Messenger
dc.subject Signal Transduction
dc.title Latent factor analysis to discover pathway-associated putative segmental aneuploidies in human cancers.
dc.title.alternative en_US
dc.type Journal Article
dc.description.version Version of Record en_US
duke.date.pubdate 2010-9-0 en_US
duke.description.endpage e1000920 en_US
duke.description.issue 9 en_US
duke.description.startpage e1000920 en_US
duke.description.volume 6 en_US
dc.relation.journal Plos Computational Biology en_US
pubs.author-url http://www.ncbi.nlm.nih.gov/pubmed/20824128
pubs.issue 9
pubs.organisational-group /Duke
pubs.organisational-group /Duke/Institutes and Provost's Academic Units
pubs.organisational-group /Duke/Institutes and Provost's Academic Units/University Institutes and Centers
pubs.organisational-group /Duke/Institutes and Provost's Academic Units/University Institutes and Centers/Social Science Research Institute
pubs.organisational-group /Duke/School of Medicine
pubs.organisational-group /Duke/School of Medicine/Basic Science Departments
pubs.organisational-group /Duke/School of Medicine/Basic Science Departments/Biostatistics & Bioinformatics
pubs.organisational-group /Duke/School of Medicine/Basic Science Departments/Molecular Genetics and Microbiology
pubs.organisational-group /Duke/School of Medicine/Basic Science Departments/Pharmacology & Cancer Biology
pubs.organisational-group /Duke/School of Medicine/Clinical Science Departments
pubs.organisational-group /Duke/School of Medicine/Clinical Science Departments/Medicine
pubs.organisational-group /Duke/School of Medicine/Clinical Science Departments/Medicine/Medicine, Rheumatology and Immunology
pubs.organisational-group /Duke/School of Medicine/Clinical Science Departments/Radiation Oncology
pubs.organisational-group /Duke/School of Medicine/Institutes and Centers
pubs.organisational-group /Duke/School of Medicine/Institutes and Centers/Duke Cancer Institute
pubs.publication-status Published online
pubs.volume 6
dc.identifier.eissn 1553-7358

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