Display Settings:

Format

Send to:

Choose Destination
Adv Cancer Res. 2003;90:91-125.

High-resolution analysis of genetic events in cancer cells using bacterial artificial chromosome arrays and comparative genome hybridization.

Author information

  • 1Roswell Park Cancer Institute, Department of Cancer Genetics, Elm and Carlton Streets, Buffalo, New York 14263, USA.

Abstract

Chromosome analysis of cancer cells has been one of the primary means of identifying key genetic events in the development of cancer. The relatively low resolution of metaphase chromosomes, however, only allows characterization of major genetic events that are defined at the megabase level. The development of the human genome-wide bacterial artificial chromosome (BAC) libraries that were used as templates for the human genome project made it possible to design microarrays containing these BACs that can theoretically span the genome uninterrupted. Competitive hybridization to these arrays using tumor and normal DNA samples reveals numerical chromosome abnormalities (deletions and amplifications) that can be accurately defined depending on the density of the arrays. At present, we are using arrays with 6,000 BACs, which provide an average resolution of less than 700 kb. Analysis of tumor DNA samples using these arrays reveals small deletions and amplifications that were not detectable by chromosome analysis and provides a global view of these genetic changes in a single hybridization experiment in 24 hours. The extent of the genetic changes can then be determined precisely and the gene content of the affected regions established. These arrays have widespread application to the analysis of cancer patients and their tumors and can detect constitutional abnormalities as well. The availability of these high-density arrays now provides the opportunity to classify tumors based on their genetic fingerprints, which will assist in staging, diagnosis, and even prediction of response to therapy. Importantly, subtle genetic changes that occur consistently in tumor cell types may eventually be used to stratify patients for clinical trials and to predict their response to custom therapies.

PMID:
14710948
[PubMed - indexed for MEDLINE]
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Loading ...
    Write to the Help Desk