Microarray Technology to Study the Role of Genetic Polymorphisms in Breast Cancer Risk

Abstract

Several studies have suggested an association between low penetrant alleles and breast cancer risk. Although the contribution of low penetrant alleles to the individual risk is relatively small, they can contribute to a large proportion of breast cancer cases in the population. In this study we took the candidate gene approach to study the association of 19 different genetic polymorphisms with breast cancer risk in a population-based sample using a high-throughput genotyping technology. To date, we have completed genotyping 398 cases and 372 population controls for 19 SNPs from several cancer-related molecular pathways. Univariate analysis has shown that XPD cod751 polymorphism is significantly associated with breast cancer risk. None of the remaining 18 SNPs were associated with breast cancer risk individually. Sub-group analysis of the cases has shown that SNPs of ER, XPD, COMT and p27 genes were significantly associated with breast cancer risk in cases with at least a first-degree relative of breast cancer. Cyp17 and MTHFR SNPs were associated with pre-menopausal status, whereas GADD45 and COMT were associated with post-menopausal status. Multivariate analysis of the sample (Logistic Regression Models and Bootstrap analysis) has shown interesting findings regarding the biological interaction between the alleles of cancer-related proteins. The stronger interaction was observed between XPD (DNA repair) and IL-10 (Immune system) SNPs (68%), whereas COMT (Estrogen metabolism) and CyclinD1 interaction shown to be 61% with the bootstrap analysis. The approach used in this study has discovered novel biological interactions between different cancer pathways in the context of breast cancer predisposition. Future studies focusing on systematic selection of functional SNPs and the investigation of their interaction in a larger and homogeneous subset of samples will provide basis for the polygenic model of breast cancer.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2004
Accession Number
ADA427756

Entities

People

  • Hilmi Ozcelik
  • Julia A. Knight

Organizations

  • Mount Sinai Hospital, Toronto

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Amino Acids
  • Breast Cancer
  • Cell Physiological Processes
  • Cells
  • Diseases And Disorders
  • Epidemiology
  • Genetic Phenomena
  • Genetic Variation
  • Genetics
  • Health Services
  • Medical Personnel
  • Multivariate Analysis
  • Neoplasms
  • Risk Factors
  • Statistical Analysis
  • Statistical Samples

Fields of Study

  • Biology

Readers

  • Molecular and genetic basis of cancer.
  • Women's Health and Cancer Risk Research: African American Women and Pregnancy Outcomes.

Technology Areas

  • Biotechnology