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Will my breast cancer spread? Discovery may predict probability of metastasis

Date:
October 26, 2011
Source:
University of Utah Health Sciences
Summary:
Researchers have discovered a new way to model human breast cancer that could lead to new tools for predicting which breast cancers will spread and new ways to test drugs that may stop its spread.

Researchers from Huntsman Cancer Institute (HCI) at the University of Utah have discovered a new way to model human breast cancer that could lead to new tools for predicting which breast cancers will spread and new ways to test drugs that may stop its spread. Their results are published online in the journal Nature Medicine.

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To create this improved model for breast cancer studies, the researchers grafted tumor tissue from consenting breast cancer patients directly into mouse mammary glands, rather than the traditional approach, where the cancer cells are grown, or cultured, in the laboratory. They discovered that the grafts remained virtually identical to the original human breast cancer in structure, genetic makeup and behavior, unlike the methods that rely on cell cultures.

"The most surprising result was that the tumor grafts spread from the original site, or metastasized, just as they did in the human patients," said the study's principal investigator Alana Welm, Ph.D., assistant professor in the Department of Oncological Sciences and an HCI investigator . "For example, grafts of tumor tissue from patients whose cancer had spread to the lung also spread to the lungs of the mice that received them."

Most breast cancer deaths result from the disease spreading to other areas of the body such as the lymphatic system, lungs, liver, bones or brain.

In addition, researchers found that the successful grafts were nearly all from patients who developed the most aggressive forms of breast cancer and ultimately died of their disease.. This result reveals the modeling method's potential as a tool that, soon after a breast cancer diagnosis, could identify whether the tumor would be likely to spread, helping doctors select the best treatment approach for an individual patient's form of the disease.

"There is also the potential to develop similar models for other cancers using this method," says Welm. "We are already working on this with colon cancer tissues."

The study is a cooperative effort of HCI's Breast Disease Oriented Team, composed of surgeons, medical and radiation oncologists, pathologists, and laboratory scientists. Other contributors included HCI's Comparative Oncology Resource, the Tissue Resource and Application Core, and ARUP Research Institute. The work was supported by funding from the U.S. Department of Defense Breast Cancer Research Program, the American Association for Cancer Research, the Breast Cancer Research Foundation, and Huntsman Cancer Foundation.


Story Source:

The above story is based on materials provided by University of Utah Health Sciences. Note: Materials may be edited for content and length.


Journal Reference:

  1. Yoko S DeRose, Guoying Wang, Yi-Chun Lin, Philip S Bernard, Saundra S Buys, Mark T W Ebbert, Rachel Factor, Cindy Matsen, Brett A Milash, Edward Nelson, Leigh Neumayer, R Lor Randall, Inge J Stijleman, Bryan E Welm, Alana L Welm. Tumor grafts derived from women with breast cancer authentically reflect tumor pathology, growth, metastasis and disease outcomes. Nature Medicine, 2011; DOI: 10.1038/nm.2454

Cite This Page:

University of Utah Health Sciences. "Will my breast cancer spread? Discovery may predict probability of metastasis." ScienceDaily. ScienceDaily, 26 October 2011. <www.sciencedaily.com/releases/2011/10/111023135719.htm>.
University of Utah Health Sciences. (2011, October 26). Will my breast cancer spread? Discovery may predict probability of metastasis. ScienceDaily. Retrieved December 18, 2014 from www.sciencedaily.com/releases/2011/10/111023135719.htm
University of Utah Health Sciences. "Will my breast cancer spread? Discovery may predict probability of metastasis." ScienceDaily. www.sciencedaily.com/releases/2011/10/111023135719.htm (accessed December 18, 2014).

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