This testing tool characterizes the protein signatures of a pancreatic cancer tumor to help determine the best treatment options. Pancreatic cancer has one of the lowest survival rates, largely due to late-stage detection and limited treatment efficacy. Clinicians routinely measure only one protein tumor marker, serum CA19-9, for diagnosis and prognosis of pancreatic cancer. Since serum CA19-9 can be elevated in the presence of other cancers and diseases, such as cirrhosis, it can be unreliable as a predictor of tumor response and patient survivability. The global market for pancreatic cancer treatment, projected to reach $4.2 billion in 2025 , requires a more reliable prognostic tool to guide treatment options.
Researchers at the University of Florida have developed a risk scoring algorithm that uses a protein signature to predict the development of pancreatic tumors. This reliable prognostic test enables a better understanding of the tumor’s environment. More personalized treatments will improve patients’ survivability and quality of life.
A clinical test that characterizes pancreatic tumors to inform personalized cancer treatment
The prognostic test uses a risk-scoring algorithm that analyzes the protein signature of a sample taken from the tumor microenvironment via fine needle aspirate biopsy. The algorithm generates a score indicative of post-surgical survival that can guide physicians in choosing from appropriate treatment options, including surgery, chemotherapy, radiation, hormone therapy, or palliative care. Physicians may also use this testing system in conjugation with other prognostic tools.
