Mechanism of Prostate Cancer Prevention by Down-Regulation of the GH/IGF Axis

Abstract

The purpose of this project was to test the hypothesis that growth hormone (GH) stimulates specific pathways, some of which are independent of IGF-I, for promoting proliferation and inhibiting death in prostate cancer cells. The first aim was to determine which of the multiple signaling pathways stimulated by GH receptor are required to promote prostate cancer. Our strategy was to cross mice that develop prostate cancers due to a large T antigen (TAg) transgene with mice that lack discrete segments of the intracellular portion of the GH receptor. We have not yet completed this experiment due to insufficient breeder fecundity but the studies should be complete by October of this year. To assess the relative contribution of IGF-I and GH to prostate carcinogenesis, we grafted prostate tissue harboring the TAg transgene. The grafts were either Ghr+/+ or Ghr-/- and therefore were able to respond to IGF-I but not detect GH. Our results suggest that IGF-I is the major driver of carcinogenesis. We also planned to propagate human prostate cancer cells in vitro and expose them to a human growth hormone antagonist. In vitro, however, the cells were neither stimulated by recombinant human GH nor inhibited by GH antagonist. Studies GH antagonist mice demonstrated that the presence of a GH antagonist can significantly retard the progression of prostate carcinogenesis driven by the powerful SV40 oncogene.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2013
Accession Number
ADA601960

Entities

People

  • Steven M. Swanson

Organizations

  • University of Illinois at Chicago

Tags

DTIC Thesaurus Topics

  • Animals
  • Biomedical Research
  • Cancer
  • Cell Line
  • Cells
  • Cellular Structures
  • Chi Square Test
  • Cultured Cells
  • Data Analysis
  • Diseases And Disorders
  • Epithelial Cells
  • Genetics
  • Laboratory Animals
  • Neoplasms
  • Prostate
  • Prostate Cancer
  • Tissues

Fields of Study

  • Biology
  • Medicine

Readers

  • Data Mining and Knowledge Discovery.
  • Immunology and Pathology
  • Molecular Biology and Genetics