Analysis of gene expression data from non-small cell lung carcinoma cell lines reveals distinct sub-classes from those identified at the phenotype level.

2.50
Hdl Handle:
http://hdl.handle.net/10033/620749
Title:
Analysis of gene expression data from non-small cell lung carcinoma cell lines reveals distinct sub-classes from those identified at the phenotype level.
Authors:
Dalby, Andrew R; Emam, Ibrahim; Franke, Raimo
Abstract:
Microarray data from cell lines of Non-Small Cell Lung Carcinoma (NSCLC) can be used to look for differences in gene expression between the cell lines derived from different tumour samples, and to investigate if these differences can be used to cluster the cell lines into distinct groups. Dividing the cell lines into classes can help to improve diagnosis and the development of screens for new drug candidates. The micro-array data is first subjected to quality control analysis and then subsequently normalised using three alternate methods to reduce the chances of differences being artefacts resulting from the normalisation process. The final clustering into sub-classes was carried out in a conservative manner such that sub-classes were consistent across all three normalisation methods. If there is structure in the cell line population it was expected that this would agree with histological classifications, but this was not found to be the case. To check the biological consistency of the sub-classes the set of most strongly differentially expressed genes was be identified for each pair of clusters to check if the genes that most strongly define sub-classes have biological functions consistent with NSCLC.
Affiliation:
Helmholtz Centre for infection research, Inhoffenstr. 7, 38124 Braunschweig, Germany.
Citation:
Analysis of gene expression data from non-small cell lung carcinoma cell lines reveals distinct sub-classes from those identified at the phenotype level. 2012, 7 (11):e50253 PLoS ONE
Journal:
PloS one
Issue Date:
2012
URI:
http://hdl.handle.net/10033/620749
DOI:
10.1371/journal.pone.0050253
PubMed ID:
23209689
Type:
Article
Language:
en
ISSN:
1932-6203
Appears in Collections:
Publications of the research group Chemical Biology (CBIO)

Full metadata record

DC FieldValue Language
dc.contributor.authorDalby, Andrew Ren
dc.contributor.authorEmam, Ibrahimen
dc.contributor.authorFranke, Raimoen
dc.date.accessioned2017-01-26T10:33:25Z-
dc.date.available2017-01-26T10:33:25Z-
dc.date.issued2012-
dc.identifier.citationAnalysis of gene expression data from non-small cell lung carcinoma cell lines reveals distinct sub-classes from those identified at the phenotype level. 2012, 7 (11):e50253 PLoS ONEen
dc.identifier.issn1932-6203-
dc.identifier.pmid23209689-
dc.identifier.doi10.1371/journal.pone.0050253-
dc.identifier.urihttp://hdl.handle.net/10033/620749-
dc.description.abstractMicroarray data from cell lines of Non-Small Cell Lung Carcinoma (NSCLC) can be used to look for differences in gene expression between the cell lines derived from different tumour samples, and to investigate if these differences can be used to cluster the cell lines into distinct groups. Dividing the cell lines into classes can help to improve diagnosis and the development of screens for new drug candidates. The micro-array data is first subjected to quality control analysis and then subsequently normalised using three alternate methods to reduce the chances of differences being artefacts resulting from the normalisation process. The final clustering into sub-classes was carried out in a conservative manner such that sub-classes were consistent across all three normalisation methods. If there is structure in the cell line population it was expected that this would agree with histological classifications, but this was not found to be the case. To check the biological consistency of the sub-classes the set of most strongly differentially expressed genes was be identified for each pair of clusters to check if the genes that most strongly define sub-classes have biological functions consistent with NSCLC.en
dc.language.isoenen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subject.meshArtifactsen
dc.subject.meshBiomarkers, Tumoren
dc.subject.meshCarcinoma, Non-Small-Cell Lungen
dc.subject.meshCell Lineen
dc.subject.meshCell Line, Tumoren
dc.subject.meshCluster Analysisen
dc.subject.meshGene Expressionen
dc.subject.meshGene Expression Profilingen
dc.subject.meshGene Expression Regulationen
dc.subject.meshGene Expression Regulation, Neoplasticen
dc.subject.meshHumansen
dc.subject.meshLung Neoplasmsen
dc.subject.meshModels, Geneticen
dc.subject.meshOligonucleotide Array Sequence Analysisen
dc.subject.meshPhenotypeen
dc.subject.meshQuality Controlen
dc.titleAnalysis of gene expression data from non-small cell lung carcinoma cell lines reveals distinct sub-classes from those identified at the phenotype level.en
dc.typeArticleen
dc.contributor.departmentHelmholtz Centre for infection research, Inhoffenstr. 7, 38124 Braunschweig, Germany.en
dc.identifier.journalPloS oneen

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