- Oral Presentation
- Open Access
High-resolution representational oligonucleotide microarray analysis and fluorescence in situ hybridization analysis of aneuploid and diploid breast tumors
© BioMed Central 2005
- Published: 17 June 2005
- Breast Cancer
- Unique Insight
- Combine Technique
- Amplification Event
- Early Stage Tumor
Combining representational oligonucleotide microarray analysis (ROMA) of tumor DNA with quantitative multigene fluorescence in situ hybridization (QM-FISH) of individual tumor cells provides the opportunity to detect and validate a wide range of gene amplifications, deletions, duplications and rearrangements directly in frozen tumor samples.
We have used these combined techniques to examine 101 aneuploid and diploid breast tumors (highly aneuploid A-tumors and pseudo-diploid D-tumors), for which long-term follow-up and detailed clinical information were available.
We have determined that ROMA provides accurate and sensitive detection of duplications, amplifications and deletions, and it yields defined boundaries for these events with a resolution of less than 50 kbp in most cases.
Diploid tumors are particularly useful subjects for this approach, revealing complex rearrangements and repeated sequential amplification events on certain chromosomes that provide unique insights into the genomic progression of the disease. First, the fine structure of these amplification clusters, as detected by ROMA and quantitatively validated by FISH, provides extremely high-resolution 'pointers' to potential novel oncogenes, since many of the detected amplicons contain only one or two known or prospective genes. Second, FISH patterns provide a means for interpretation of the mechanism of these events. Third, the reproducibility and frequency of these events, especially in very early stage tumors, provides insight into the earliest chromosomal events in breast cancer. Finally, we have identified correlations between certain sets of rearrangement events and clinically relevant parameters such as long-term survival. These correlations may enable novel and powerful prognostic indicators for breast cancer and other cancers when more samples can be examined.