Read about HCI's ground-breaking research in sarcoma, a rare form of cancer.

Read Understanding the Genesis of Colon Cancer Through Enzymatic Processes in the University of Utah's 2011 Annual Donor Report.

Precise, accurate imaging—think mammography, CT and MRI scans—is important to cancer screening, treatment, and follow-up care. Now, even more advanced technology is emerging, and with it, the need for imaging specialists with the expertise to use them.

Huntsman Cancer Institute (HCI) at the University of Utah has demonstrated particular excellence in the field, as demonstrated by the National Cancer Institute (NCI) naming HCI a Center for Quantitative Imaging Excellence (CQIE). This designation is only available to NCI-Designated Cancer Centers; HCI is the only NCI-Designated Cancer Center in the five-state Intermountain West.

Quantitative imaging involves imaging at the molecular and cellular level with positron emission tomography (PET), using volumetric computed tomography (vCT), volumetric magnetic resonance imaging (vMRI), and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

According to NCI, the CQIE program was necessary to establish standard operating procedures and guidelines for the new technology that would be uniform across the entire NCI network of cancer centers. Once a center has earned CQIE certification, it is deemed "trial ready," and capable of conducting NCI-sponsored clinical trials that use advanced quantitative imaging. Before, there were significant delays in the time required to open a clinical trial when the advanced imaging technology was needed.

"As Huntsman Cancer Institute works to provide new approaches to individualized cancer diagnosis and therapy through clinical trials, the ability to provide our patients with cutting edge technology and highly trained specialists is becoming more and more important," says Mary Beckerle, HCI's CEO and director. "The attainment of this credential is essential to our continued progress toward the goal of personalized cancer care."

Beckerle credits John M. Hoffman, M.D., co-leader of HCI's Imaging, Diagnostics, and Therapeutics Research Program and a professor of radiology and neurology at the University of Utah, for his work to obtain the NCI credential. Each approved CQIE center must be recertified annually.

For more information about the NCI initiative, please visit http://www.acrin.org/CORELABS/NCICQIEQUALIFICATIONPROGRAM.aspx

HCI investigator Wallace Akerley, MD, discusses the causes and treatments for lung cancer.

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 today in the journal Nature Medicine.

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, comprised 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.

Utah technique could one day predict aggressive breast cancer
Read the article at The Salt Lake Tribune

HCI Investigator Wins Presidential Award
HCI investigator Nicola Camp, PhD, has received a 2010 Presidential Early Career Awards for Scientists and Engineers. The award is given to... Read Story >>>

Novel Analysis Method Organizes Genomic Cancer Data
The technology that allows scientists to profile the entire genome of individual tumors offers new hope for...  Learn More >>>

HCI investigator Nicola Camp, PhD, has received a Presidential Early-Career Award for Scientists and Engineers. The award is given to science and engineering professionals in the early stages of their independent research careers. According to a White House press release, "The Presidential early career awards embody the high priority the Obama Administration places on producing outstanding scientists and engineers to advance the Nation's goals, tackle grand challenges, and contribute to the American economy."

Camp says she is "beaming from ear to ear. To be recognized by your peers about something that has the potential to make a difference—it's just a great feeling."

Camp is a professor in the Division of Genetic Epidemiology, Department of Biomedical Informatics at the University of Utah and a member of the Cancer Control and Population Sciences Program. Her research focuses on identifying genes involved in the predisposition and risk modification for or survivorship of common cancers such as prostate cancer, multiple myeloma, breast cancer, colon cancer, and chronic lymphocytic leukemia.

Originally trained as a mathematician and statistician, Camp uses those skills to develop methods of analyzing genome data. To be recognized for this type of work is huge, says Camp, because it's an area that often doesn't receive as much attention as laboratory and clinical research.

"Translating our understanding of disease mechanisms into something we can put into clinical practice is not going to happen unless we have the most state-of-the-art methods to actually do that analysis," Camp explains. "So it's nice to have acknowledgment for that particular part of the field. I think people are realizing how important it is."

Camp and the other recipients accepted their awards in Washington, D.C., in October 2011.

SALT LAKE CITY—The technology that allows scientists to profile the entire genome of individual tumors offers new hope for discovering ways to select the best treatment for each patient's particular type of cancer. However, these profiles produce huge amounts of data, and the volume alone creates unique analytical problems.

In a study published on-line this week in the journal BMC Medical Genomics, researchers from Huntsman Cancer Institute (HCI) at the University of Utah describe a new analytical approach based on a concept called multiplicity, that can organize large amounts of varied genetic data. The method allows researchers to create three-dimensional models revealing previously unknown relationships among the genes involved with different types of cancer.

"This technique shows similar genetic profiles for different types of cancers, which could open the door to trials of already approved drugs for additional cancers," said Lewis Frey, PhD, assistant professor in the Department of Biomedical Informatics and an HCI investigator. "It can bring to light previously unknown genetic connections between different cancers, helping focus the search for cancer-causing genetic mutations. It makes whole genome data more usable for both clinical and laboratory researchers."

Stephen R. Piccolo, Ph.D., a postdoctoral research associate in the Department of Biomedical Informatics at the University of Utah, and Mary E. Edgerton, M.D., Ph.D., associate professor in the Department of Pathology at MD Anderson Cancer Center in Houston, Texas, are co-authors of the article. The study was funded in part by an Incentive Seed Grant from the University of Utah, and a National Library of Medicine training grant.