Identification of transcriptional biomarkers induced by SERMS in human endometrial cells using multivariate analysis of DNA microarrays

Biomarkers. 2004 Nov-Dec;9(6):447-60. doi: 10.1080/13547500400022192.

Abstract

Functional genomic tools such as DNA microarrays are having a major impact on the drug-discovery process. Potentially, compounds with toxic responses can be identified and removed at a relatively early stage in the drug-development process before tests on animals or humans, solely on the gene expression profiles produced in cell culture. The study examined the expression profiles of primary cultured human endometrial cells treated with 17beta-oestradiol and the SERMs (selective oestrogen receptor modulators) tamoxifen and raloxifene. Primary cultures from three individuals were split into glandular epithelial cells and stromal cell types. Principal components and partial least-squares-discriminate analyses were employed to examine the transcript profile as a whole, identifying genes responsible for patient separation and those that might have an important role in tamoxifen-associated carcinogenesis. Using multivariate data analysis, transcriptional responses were identified in epithelial cells but not in stromal cells for the three SERMs examined. However, it was demonstrated that a major problem associated with using primary cultures derived from human patients is the large transcriptional differences that might exist between the different cultures.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Analysis of Variance
  • Biomarkers*
  • Cells, Cultured
  • Endometrium / drug effects
  • Endometrium / metabolism*
  • Estradiol / metabolism
  • Female
  • Humans
  • Least-Squares Analysis
  • Multivariate Analysis
  • Oligonucleotide Array Sequence Analysis
  • RNA / metabolism
  • RNA, Messenger / metabolism
  • Selective Estrogen Receptor Modulators / pharmacology*
  • Time Factors
  • Transcription, Genetic*

Substances

  • Biomarkers
  • RNA, Messenger
  • Selective Estrogen Receptor Modulators
  • Estradiol
  • RNA