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Application of gene expression profiling to colon cell maturation, transformation and chemoprevention

  • Leonard H. Augenlicht
  • , Anna Velcich
  • , Lidija Klampfer
  • , Huang Jie
  • , Georgia Corner
  • , Maria Aranes
  • , Christian Laboisse
  • , Basil Rigas
  • , Martin Lipkin
  • , Yang Kan
  • , Shi Quihu
  • , Martin Lesser
  • , Barbara Heerdt
  • , Diego Arango
  • , Wan Cai Yang
  • , Andrew Wilson
  • , John M. Mariadason
  • Albert Einstein College of Medicine
  • Nantes Université
  • Strang Cancer Prevention Center
  • New York Medical College
  • Northwell Health System

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Methods for high-throughput analysis of profiles of gene expression that assay thousands of genes simultaneously are powerful approaches for understanding and classifying cell and tissue phenotype. This includes analysis of normal pathways of cell maturation and their perturbation in transformation, the sensitivity and mechanism of response of normal and tumor cells to physiological and pharmacological agents, and modulation of tumor risk and progression by nutritional factors. However, the complex data generated by such approaches raise difficulties in analysis. We will describe some of the methods we have used in analyzing databases generated in a number of projects in our laboratories. These include: the role of k-ras mutations in colon cell transformation; the role of p21wAF1/cip1 in intestinal tumor formation and response to sulindac; the development of the absorptive and goblet cell lineages; sensitivity of colonic cells to chemotherapeutic agents; mechanisms that regulate c-myc expression utilizing novel methods of transcriptional imaging; and interaction of nutritional and genetic factors in modulation of intestinal tumor formation.

Original languageEnglish
Pages (from-to)2410S-2416S
JournalJournal of Nutrition
Volume133
Issue number7 SUPPL.
DOIs
StatePublished - Jul 1 2003

Keywords

  • Gene profiling
  • Intestinal cancer
  • Microarrays
  • Muc2
  • p21

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