Mammary Cancer and Activation of Transposable Elements

Abstract

The purpose of this project is to investigate molecular events of the preclinical stages of mammary cancer, specifically, the intersection between the development of genome demethylation, retrotransposon transcriptional activity, and retrotransposon-driven transcription of cellular genes in an engineered parity-dependent mouse model of mammary cancer. These inbred mice develop mammary cancer after 3 litters. Mammary epithelial cells (MEC) were isolated from cancer-prone and control mice after 1 or 3 litters. DNA and RNA were isolated from the MEC. Data from Illumina HiSeq RNA libraries was forwarded to our collaborator Dr John Edwards for transcriptome analysis. DNA from MEC was sent to Dr Edwards for processing and methylome analysis. As expected, using Methyl-MAPS analysis, Dr Edwards identified whole genome hypomethylation in tumor-prone MEC compared with controls after 3 litters. We did not identify increased retrotransposon expression. An unexpected and intriguing observation was upregulated expression of immune system suppressors in tumor-prone MEC after 3 litters. Wet lab independent confirmation of the findings is pending, and forms part of the research plan for a doctoral student in Adelaide. Our data suggest that while hypomethylation is an early event in this model, upregulated retrotransposon expression is a later event, and unlikely to play a direct role in cancer ontogeny.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2015
Accession Number
AD1001608

Entities

People

  • Anne Peaston

Organizations

  • University of Adelaide

Tags

DTIC Thesaurus Topics

  • Biomedical Research
  • Breast Cancer
  • Cell Physiological Processes
  • Cells
  • Epithelial Cells
  • Gene Expression
  • Health Services
  • Immune System
  • Mammary Glands
  • Materials
  • Medical Personnel
  • Neoplasms
  • Research Facilities

Fields of Study

  • Biology

Readers

  • Molecular Genetics
  • Molecular and Cellular Biology
  • Oncology and Biomarker-Based Cancer Detection.