Multiple comparisons model-based clustering and ternary pattern tree numerical display of gene response to treatment: Procedure and application to the preclinical evaluation of chemopreventive agents

Thomas R. Sutter, Xiao Rui He, Peter Dimitrov, Lijing Xu, Giri Narasimhan, E. Olusegun George, Carrie Hayes Sutter, Clinton Grubbs, Richard Savory, Markus Stephan-Gueldner, Dirk Kreder, Michael J. Taylor, Ronald Lubet, Tricia A. Patterson, Thomas W. Kensler

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Microarray technology has greatly aided the identification of genes that are expressed differentially. Statistical analysis of such data by multiple comparisons procedures has been slow to develop, in part, because methods to cluster the results of such comparisons in biologically meaningful ways have not been available. We isolated and analyzed, by Northern blot and GeneChip, replicate liver RNA samples (n = 4/group) from rats fed with control diet or diet containing one of three chemopreventive compounds, selected because their pharmacological activities, including RNA expression response, are relatively well understood. We report on a classification tree, based on the results of nonparametric multiple comparisons, which results in the bipolar hierarchical clustering of genes in relation to their response to treatment. In addition to identifying treatment-responsive genes, application of this procedure to our test study identified the known pharmacological relationships among the treatment groups without supervision. Also, small treatment-specific subsets of genes were identified that may be indicative of additional pharmacophores present in the test compounds.

Original languageEnglish (US)
Pages (from-to)1283-1292
Number of pages10
JournalMolecular cancer therapeutics
Volume1
Issue number14
StatePublished - Dec 2002

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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