Under the Microscope: Accelerating the Road to Precision Medicine in Breast Cancer and Beyond

Until recently, patients with a certain stage and type of tumor all received similar treatments. Now, cancer treatments can be personalized to some extent, but there is still a great deal of untapped potential for using information about genetics and gene expression to guide doctors to the therapies with the best possible chance of success.

With support from the V Foundation, Charles Perou and his research team at the University of North Carolina Lineberger (UNC) Comprehensive Cancer Center are working to greatly expand the number of biomarkers, or molecular signatures, that doctors can use to determine the best treatment for a specific person’s cancer. Perou, the May Goldman Shaw Distinguished Professor of Molecular Oncology and co-director of the UNC Computational Medicine Program, is widely known for demonstrating that breast cancer is not one disease but is instead multiple distinct subtypes with different gene expression patterns.

The V Foundation has awarded more than $30 million in breast cancer research grants. These groundbreaking studies seek to bring new treatments and diagnosis strategies from the lab to the clinic, examine never-before-studied facets of breast cancer, boost enrollment in important clinical trials and help breast cancer survivors.

From the bench to bedside

In the past five to seven years, panels of DNA-based biomarkers have been developed that can help doctors decide the best therapy for certain cancers. Perou’s work builds on this by examining more than 800 gene expression signatures to figure out which ones might be useful for making clinical decisions. Some of these gene expression signatures were discovered in Perou’s laboratory, where researchers use their expertise in breast cancer to develop treatments specific to each patient and tumor.

Perou points out that it is a long process to develop a clinical test that can be used to make patient treatment decisions. Every step needs to be well-validated and documented. In five to 10 years, this new research could lead to a single medical test that reveals treatment-relevant biomarkers for solid tumors such as breast and lung cancers, melanoma and head and neck cancers. This type of precision medicine would help make sure patients receive the best therapies for their tumor while sparing them from treatments that are unlikely to help.

“I’m very thankful to the V Foundation for providing support along this path because, in large part, conventional funding sources do not fund research that falls between basic research and clinical research,” said Perou. “By funding this type of translational research, the V Foundation is helping move basic research knowledge into the clinic as fast as possible.”

Saving lives and lowering healthcare costs

The gene expression signatures Perou is studying include ones that reveal whether immune cells are present in a tumor. These immune cell signatures could provide a way to decide who should get therapies targeting immune cells, which cost more than $100,000 per patient per year. Understanding exactly who will benefit from this type of therapy would help ensure the right patients receive it and save healthcare costs by not giving it to patients who wouldn’t benefit from it.

“Our preliminary data suggest that we may have a new biomarker that would help decide who gets immune therapy and who doesn’t,” said Perou. “We have a number of years to go before we could formally show that with the needed clinical rigor, but we’re going down a promising, exciting path to move this information closer to being used in the clinic.”

To figure out which gene expression signatures could be used to make therapy decisions, the researchers had to first develop a valid and repeatable analysis method, or assay. They are now testing this assay in a clinical laboratory using tumor samples from patients who had cancer in the past to figure out which signatures could be of value.

“The V Foundation grant gave us the wherewithal to show the technical feasibility of our approach and to figure out some of the complicated computational methods it requires,” said Perou. “Now that we know which technology is best and have the computational tools in hand, we can use them in the clinical laboratory to produce an assay that can be used for early clinical testing.”