Characterization of a New In Vivo Prostate Tumor Model that Progresses to Androgen-Independence and its Application in Determining Changes in Gene Expression

Abstract

Investigation of the molecular events underlying progression of prostate cancer to androgen-independence has been impeded by the lack of an in vivo model that yields pure populations of prostate cancer cells that are not contaminated with host cells. Here we characterize a new in vivo model that employs hollow fibers and allows for the retrieval of uncontaminated prostate cancer cells during various stages of endocrine progression to androgen-independence. Prostate-specific antigen (PSA) gene expression, proliferation of cells, and histology were examined before and after castration of the host Approximately 5xlO LNCaP prostate cancer cells/animal provided measurable levels of PSA in the serum that increased in intact (non-castrated) animals, decreased 80% to a nadir following castration, and subsequently increased by 4 weeks after castration indicating progression to androgen-independence. In vivo proliferation of LNCaP cells inside fibers continued in the presence of androgens and continued to increase, albeit at a slower rate, in castrated animals Gene expression patterns in this model were consistent with clinical samples and other models when using cDNA arrays to screen RNA isolated from the model Approximately 150 genes were identified to be altered during progression to androgen independence with 77 of these genes having unknown function.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2002
Accession Number
ADA413293

Entities

People

  • Marianne D. Sadar

Organizations

  • BC Cancer Agency

Tags

DTIC Thesaurus Topics

  • Androgen Receptors
  • Androgens
  • Blood
  • Cells
  • Chemistry
  • Endocrine Cells
  • Epithelial Cells
  • Gene Expression
  • Genetics
  • Growth Factors
  • Health Services
  • Neoplasms
  • Peptide Growth Factors
  • Prostate
  • Proteins
  • Therapy
  • Tissues

Fields of Study

  • Biology

Readers

  • Mathematics or Statistics
  • Molecular Genetics
  • Prostate Cancer Biology.