High Resolution Analysis of Copy Number Mutation in Breast Cancer

Abstract

Cancer is a disease associated with both germline and somatic mutation, and undoubtedly evolves in the host through increasingly malignant states by changes in the genome. Many of these changes can be seen by making gene copy number measurements, wherein increased copies of genes are associated with oncogenes and decreased copy numbers are associated with tumor suppressor genes. It is our hypothesis that these copy number changes, if measured with sufficient accuracy and resolution, can be used for two important purposes: to define precisely the mutant genes that cause cancer, and to define molecular markers that correlate with malignant potential and response to therapy. The technique we have developed, ROMA (representational oligonucleotide microarray analysis), accomplished this. We have completed data acquisition of approximately 200 breast cancer biopsies and cell lines. We discern many loci that are commonly deleted or amplified in breast cancer but not in normal genomes. Many of these loci confirm previous knowledge, but many are as yet unexplained. Our studies further suggests that genome instability, the presence of amplifications and deletions, is a marker for poor survival, and we have developed mathematical measures of copy number profiles that accurately predict.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
May 01, 2005
Accession Number
ADA438392

Entities

People

  • Michael H. Wigler

Organizations

  • Cold Spring Harbor Laboratory

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Carcinoma
  • Cells
  • Chemical Synthesis
  • Chemistry
  • Chromosomes
  • Computational Science
  • Databases
  • Dna Microarrays
  • Generative Models
  • Genetic Variation
  • Genetics
  • Hidden Markov Models
  • Information Science
  • Mathematical Models
  • Medical Personnel
  • Microarray Analysis
  • Probability

Fields of Study

  • Biology

Readers

  • Computational Modeling and Simulation
  • Molecular and genetic basis of cancer.