Literature DB >> 10700174

Systematic variation in gene expression patterns in human cancer cell lines.

D T Ross1, U Scherf, M B Eisen, C M Perou, C Rees, P Spellman, V Iyer, S S Jeffrey, M Van de Rijn, M Waltham, A Pergamenschikov, J C Lee, D Lashkari, D Shalon, T G Myers, J N Weinstein, D Botstein, P O Brown.   

Abstract

We used cDNA microarrays to explore the variation in expression of approximately 8,000 unique genes among the 60 cell lines used in the National Cancer Institute's screen for anti-cancer drugs. Classification of the cell lines based solely on the observed patterns of gene expression revealed a correspondence to the ostensible origins of the tumours from which the cell lines were derived. The consistent relationship between the gene expression patterns and the tissue of origin allowed us to recognize outliers whose previous classification appeared incorrect. Specific features of the gene expression patterns appeared to be related to physiological properties of the cell lines, such as their doubling time in culture, drug metabolism or the interferon response. Comparison of gene expression patterns in the cell lines to those observed in normal breast tissue or in breast tumour specimens revealed features of the expression patterns in the tumours that had recognizable counterparts in specific cell lines, reflecting the tumour, stromal and inflammatory components of the tumour tissue. These results provided a novel molecular characterization of this important group of human cell lines and their relationships to tumours in vivo.

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Year:  2000        PMID: 10700174     DOI: 10.1038/73432

Source DB:  PubMed          Journal:  Nat Genet        ISSN: 1061-4036            Impact factor:   38.330


  596 in total

1.  Comparative genome-scale analysis of gene expression profiles in T cell lymphoma cells during malignant progression using a complementary DNA microarray.

Authors:  S Li; D T Ross; M E Kadin; P O Brown; M A Wasik
Journal:  Am J Pathol       Date:  2001-04       Impact factor: 4.307

2.  A multivariate insight into the in vitro antitumour screen database of the National Cancer Institute: classification of compounds, similarities among cell lines and the influence of molecular targets.

Authors:  G Musumarra; D F Condorelli; A S Costa; M Fichera
Journal:  J Comput Aided Mol Des       Date:  2001-03       Impact factor: 3.686

3.  Correlation between apoptosis microarray gene expression profiling and histopathological lymph node lesions.

Authors:  J P Dales; J Plumas; F Palmerini; E Devilard; T Defrance; A Lajmanovich; V Pradel; F Birg; L Xerri
Journal:  Mol Pathol       Date:  2001-02

4.  Genome-wide expression profiling of mid-gestation placenta and embryo using a 15,000 mouse developmental cDNA microarray.

Authors:  T S Tanaka; S A Jaradat; M K Lim; G J Kargul; X Wang; M J Grahovac; S Pantano; Y Sano; Y Piao; R Nagaraja; H Doi; W H Wood; K G Becker; M S Ko
Journal:  Proc Natl Acad Sci U S A       Date:  2000-08-01       Impact factor: 11.205

5.  Finding genes in the C2C12 osteogenic pathway by k-nearest-neighbor classification of expression data.

Authors:  Joachim Theilhaber; Timothy Connolly; Sergio Roman-Roman; Steven Bushnell; Amanda Jackson; Kathy Call; Teresa Garcia; Roland Baron
Journal:  Genome Res       Date:  2002-01       Impact factor: 9.043

6.  Statistical evaluation of differential expression on cDNA nylon arrays with replicated experiments.

Authors:  R Herwig; P Aanstad; M Clark; H Lehrach
Journal:  Nucleic Acids Res       Date:  2001-12-01       Impact factor: 16.971

7.  Chemosensitivity prediction by transcriptional profiling.

Authors:  J E Staunton; D K Slonim; H A Coller; P Tamayo; M J Angelo; J Park; U Scherf; J K Lee; W O Reinhold; J N Weinstein; J P Mesirov; E S Lander; T R Golub
Journal:  Proc Natl Acad Sci U S A       Date:  2001-09-11       Impact factor: 11.205

8.  Arrays of arrays for high-throughput gene expression profiling.

Authors:  P P Zarrinkar; J K Mainquist; M Zamora; D Stern; J B Welsh; L M Sapinoso; G M Hampton; D J Lockhart
Journal:  Genome Res       Date:  2001-07       Impact factor: 9.043

9.  Core biopsies can be used to distinguish differences in expression profiling by cDNA microarrays.

Authors:  Christos Sotiriou; Chand Khanna; Amir A Jazaeri; David Petersen; Edison T Liu
Journal:  J Mol Diagn       Date:  2002-02       Impact factor: 5.568

10.  Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation.

Authors:  Yee Hwa Yang; Sandrine Dudoit; Percy Luu; David M Lin; Vivian Peng; John Ngai; Terence P Speed
Journal:  Nucleic Acids Res       Date:  2002-02-15       Impact factor: 16.971

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