Biomarkers For Breast Cancer Based On Genetic Instability
Background:
The National Cancer Institute's Genetics Branch is seeking
statements of capability or interest from parties interested in
collaborative research to further develop, evaluate, or
commercialize prognostic tests for breast cancer based on a 12-gene
expression signature.
Technology:
It is difficult to establish a prognosis for breast cancer because
the clinical course and survival times of patients with the disease
vary greatly. When cells are unable to repair minor damage to
their DNA, genetic instability occurs, which can produce gross
abnormalities in chromosomes and the onset of cancer. Because
the magnitude of the abnormalities is strongly correlated with a
negative prognosis for cancer, genetic instability can serve as a
useful biomarker for establishing a prognosis for breast cancer
patients. Presently, genetic instability is not directly
accounted for in established prognostic tests.
Investigators at the National Cancer Institute (NCI) have developed
a compact gene signature that identifies genome instability in
breast cancer cells. By comparing changes in expression
levels of only 12 genes in malignant tissue to levels in normal
breast tissue, it is possible to detect the genetic abnormalities
that are indicative of a poor prognosis. This method has the
potential to improve markedly the forecasting of clinical outcomes
for breast cancer and help improve treatment of this disease.
Further R&D Needed:
- Validate the impact of the 12-genes signature in prospective
clinical trials
R&D Status: Pre-clinical and clinical
data available
IP Status:
- U.S. Provisional Application No. 61/097,101 filed 15 Sep
2008
Value Proposition:
- Reduced number of genes to monitor compared to available
technologies
- Precise staging of women with breast cancer prior to commencing
treatment
- Ability to develop therapeutics that alter genomic instability
and improve breast cancer prognosis
- Prognosis independent of other cancer indicators, such as lymph
node status
- Improved prediction in low risk patients
Contact Information:
John D. Hewes, Ph.D.
NCI Technology Transfer Center
Tel: 301-435-3121
Email: hewesj@mail.nih.gov
Please reference advertisement #809
Revised 2/23/2009