Literature DB >> 15905688

Tumor heterogeneity affects the precision of microarray analysis.

Maureen O'Sullivan1, Vikram Budhraja, Yoel Sadovsky, John D Pfeifer.   

Abstract

Microarray-based analysis of global gene expression patterns defines groups of genes that correlate with specific tumor types and prognosis, but the identified genes may not all be of equal clinical utility due to technical factors that affect the precision of their measurement. To analyze how technical variability in measured expression levels may impact microarray-based analysis in a clinical setting, we used Ewing sarcoma/peripheral neuroectodermal tumor (EWS/PNET) in a model system that replicates the clinical scenario in which microarray-based analysis of gene expression will likely occur, namely analysis of a fresh tumor sample by a single chip. By comparing variability of measured expression due to purely technical factors with variability due to biologic factors, we confirm that variability is dependent on the level of gene expression. We also demonstrate that the variability in expression level from either cell line or tumor samples is significantly higher than can be attributed to specific probe sets that have an intrinsically poor performance. These results have significant impact on the application of cDNA microarray chip for molecular analysis performed in a clinical setting.

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Year:  2005        PMID: 15905688     DOI: 10.1097/01.pas.0000158988.46025.f6

Source DB:  PubMed          Journal:  Diagn Mol Pathol        ISSN: 1052-9551


  5 in total

Review 1.  Standards affecting the consistency of gene expression arrays in clinical applications.

Authors:  Steven A Enkemann
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2010-03-23       Impact factor: 4.254

2.  Intratumor heterogeneity in evolutionary models of tumor progression.

Authors:  Rick Durrett; Jasmine Foo; Kevin Leder; John Mayberry; Franziska Michor
Journal:  Genetics       Date:  2011-03-15       Impact factor: 4.562

3.  A global meta-analysis of microarray expression data to predict unknown gene functions and estimate the literature-data divide.

Authors:  Jonathan D Wren
Journal:  Bioinformatics       Date:  2009-05-15       Impact factor: 6.937

4.  Immunohistochemical Estimates of Angiogenesis, Proliferative Activity, p53 Expression, and Multiple Drug Resistance Have No Prognostic Impact in Osteosarcoma: A Comparative Clinicopathological Investigation.

Authors:  Flemming Brandt Sorensen; Kenneth Jensen; Michael Vaeth; Henrik Hager; Anette Mariane Daa Funder; Akmal Safwat; Johnny Keller; Mariann Christensen
Journal:  Sarcoma       Date:  2009-02-25

5.  Acquisition of biologically relevant gene expression data by Affymetrix microarray analysis of archival formalin-fixed paraffin-embedded tumours.

Authors:  K M Linton; Y Hey; E Saunders; M Jeziorska; J Denton; C L Wilson; R Swindell; S Dibben; C J Miller; S D Pepper; J A Radford; A J Freemont
Journal:  Br J Cancer       Date:  2008-04-01       Impact factor: 7.640

  5 in total

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