APPLICATIONS OF TECHNOLOGY:

• Identifying breast cancer patients likely to relapse
• Selecting patients for specific breast cancer treatments

ADVANTAGES:

• Provides results independent of estrogen receptor (ER) status
• Validated across independent datasets
• Easily assesses a small number of genes

ABSTRACT:

In earlier research, Mina Bissell and colleagues at Berkeley Lab developed a three-dimensional (3D) cell culture model that mimics cellular characteristics of a human mammary gland. In this invention, the researchers combined the 3D cell culture model with a novel, unsupervised method to identify a gene signature that accurately predicts breast cancer outcome in independent datasets. The technology is based on the concept that gene expression associated with the formation of human mammary acini (cell clusters) is opposite that which occurs during development of breast tumors with poor prognosis.

Approximately 30% of early stage breast cancer patients will relapse, yet there has been no way to accurately identify these patients. Predictive gene signatures, while viewed as a valuable tool in evaluating clinical prognosis in breast cancer patients, have been shown in the past to be highly dependent on the specific set of patients studied. Until now, gene signatures have also fallen short of identifying the genes relevant to breast cancer progression.

The Berkeley Lab invention holds prognostic value for both ER-positive and ER-negative breast cancer. The approach may also be used to predict outcome for other types of cancer besides breast cancer.

STATUS:

• Patent pending. Available for licensing or collaborative research.

To learn more about licensing a technology from LBNL see http://www.lbl.gov/Tech-Transfer/licensing/index.html.

FOR MORE INFORMATION:

Martin, Katherine J., Patrick, Denis R., Bissell, Mina J., Fournier, Marcia V., “Prognostic Breast Cancer Signature Identified from 3D Culture Model Accurately Predicts Clinical Outcome across Independent Datasets, PloS One, 3 (8), e2994 (2008).

REFERENCE NUMBER: JIB-2638

SEE THESE OTHER BERKELEY LAB TECHNOLOGIES IN THIS FIELD:

• ANXA9, A Therapeutic Target and Predictive Marker for Early Detection of Aggressive Breast Cancer, JIB-2371
• Comprehensive Prognostic Markers and Therapeutic Targets for Drug-Resistant Breast Cancers, IB-2281
• Non-Transgenic Cell Lines for Identifying Target Premalignant Genes, IB-2023
• Rac1b: A Highly Selective Marker and Target for Cancer, IB-2167
• Prognostic for Invasive and Metastatic Cancers, IB-1637