Evaluation of Genomic Instability as an Early Event in the Progression of Breast Cancer

Abstract

We have shown in two independent retrospective studies that loss of telomere DNA content (TC) has potential value in predicting clinical outcome in breast cancer. However, an alternative marker for TC, which could be assessed in samples with small numbers of cells, such as fine needle aspirates, with commonly used methods is desirable. The aim of this study was to demonstrate that measurement of allelic imbalance (AI), which could be easily adapted to the clinical laboratory setting, could serve as a surrogate for TC, discriminating between women in need of more aggressive treatment and those for whom aggressive protocols are unnecessary. The candidate has developed a robust assay to determine the extent of AI that discriminates between normal and tumor specimens with 67% sensitivity and 99% specificity. Additionally, the candidate has shown that increased AI and altered TC are present in both tumors and surrounding histologically normal breast tissues at distances at least one centimeter from the visible tumor margins and decrease as a function of distance. In addition to evaluating a potential biomarker of breast cancer progression, the proposed investigation has provided the candidate opportunities to interact with pathologists and oncologists to learn normal and abnormal breast morphology, the strengths and limitations of currently used breast cancer biomarkers and the scientific rationale for ongoing clinical trials. To date, all tasks, as outlined in the Statement of Work, have been completed or partially completed.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2008
Accession Number
ADA496416

Entities

People

  • Christopher M Heaphy
  • Jeffrey K. Griffith

Organizations

  • University of New Mexico

Tags

DTIC Thesaurus Topics

  • Biomedical Research
  • Breast Cancer
  • Capillary Electrophoresis
  • Carcinoma
  • Cells
  • Chemistry
  • Chromosome Aberrations
  • Chromosomes
  • Genetics
  • Genomic Instability
  • Health Services
  • Medical Personnel
  • Neoplasms
  • Oncology
  • Proteins

Fields of Study

  • Medicine

Readers

  • Oncology and Biomarker-Based Cancer Detection.
  • Systems Analysis and Design