Early Biology, Early Detection and Benign Disease

One of the main reasons for the low survival rate of pancreatic cancer is that patients are often diagnosed at late stage where the cancer has already spread. When this disease is detected early, survival can be significantly improved.

By applying what we learn in the laboratory and leveraging our clinical resources, such as the Oregon Pancreatic Tissue Registry, we will be able to develop and validate new diagnostic tests.  Our early detection efforts include both academic and industry collaborations to rapidly move new tests into clinical practice. We are closely aligned with the Knight Cancer Institute's Cancer Early Detection Advanced Research (CEDAR) center.

Ongoing Research Projects

MRF is a pattern matching imaging method that allows for mapping of multiple parameters with a single scan. Radiologist Dr. Alexander Guimaraes has developed this system so that it does not require injections of contrast dye, is short in duration, and is unaffected by breath motion. MRF is able to distinguish changes associated with early pancreas disease like fibrosis, making it an ideal imaging system for early disease detection. We plan to further develop this approach using computational methods (machine learning) to detect additional early changes in the pancreas through long-term surveillance of at-risk patients.

The Brenden-Colson Center for Pancreatic Care supports research to develop screens for signposts of pancreatic diseases, also known as biomarkers, in a patient’s blood for early detection of pancreatic diseases.

Extracellular vesicles (EVs) are submicron-sized particles secreted by cells. Currently, we are developing approaches to identify EVs released from pancreatic cells to determine the presence or absence of early stage pancreatic cancer. Through use of high-resolution flow cytometry, pathologist Dr. Terry Morgan has been able to identify markers of EVs that are distinct in patients with pancreatic cancer, which research scientist Dr. Stuart Ibsen has been able to validate with a separate technique using  dielectrophoresis chips. Chip production in being done in collaboration with Biological Dynamics, which specializes in rapidly recovering EVs from patients’ blood. We are also collaborating with Biological Dynamics to advance a separate EV-based biomarker signature for early detection of pancreatic cancer.

  • MRF for pancreatitis – Alex Guimaraes & Cory Wyatt
  • Activity MRI for diffusion weighted imaging – Charles Springer
  • Circulating protease activity for pancreatic cancer detection – Jared Fischer
  • Identification of pancreatic cancer early detection biomarkers using exosomes, cell-free RNA, DNA signatures, and platelet activation – Terry Morgan, Thuy Ngo, Stuart Ibsen, & Sam Yunga
  • Exosome protein marker signature for early detection – Rosie Sears, Stuart Ibsen, & Zeev Ronai
  • Circulating hybrid cell detection in pre-cancer and early cancer – Melissa Wong
  • Identification of pre-malignant lesion biomarkers using signaling network mapping – John Muschler & Emek Demir
  • Activity monitors as early indicator of disease – Aaron Grossberg
  • Using tissue microarrays from patient samples to study pancreatic cancer progression – Rosalie Sears
  • Human pancreatic cancer cellular model to understand cancer initiation – Jungsun Kim
  • Aberrant mitochondrial proteins in pancreatic cancer initiation and progression – Matthew Rames
  • Identifying biomarkers of rapid recurrence – Patrick Worth