Firpo(ChemotherapyAdvisor) – A highly accurate, blood-based diagnostic panel comprising 40 individual serum biomarkers of pancreatic adenocarcinoma would provide high specificity while allowing for heterogeneity among patients and tumor characteristics, investigators reported June 19 at the American Association for Cancer Research’s Pancreatic Cancer: Progress and Challenges conference, Lake Tahoe, NV.

“Recent efforts to identify individual biomarkers or biomarker panels have been disappointing,” noted Matthew Firpo, PhD, of Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT. One drawback to use of current biomarkers is the unacceptable level of false-positive diagnoses. “Furthermore, it is unlikely that an individual biomarker will provide sufficient accuracy for detection of pancreatic adenocarcinoma given the high amount of molecular heterogeneity in the disease.”

Since cases of pancreatic adenocarcinoma are rare, a diagnostic test with only a 95% specificity would have the potential to result in upwards of 3 million people in the United States ≥50 years of age with a false-positive identification of the disease annually. Any test deployed to the general population, therefore, must have an accuracy of >99%.

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He and his colleagues developed a model using characteristics of nine individual serum biomarkers of pancreatic adenocarcinoma—relatively weak when used singly—to delineate the number of biomarkers required for accurate detection of the disease. These included AXL, CA 19-9, haptoglobin, hyaluronic acid, MMP-7, MMP-11, osteopontin, serum amyloid A, and TIMP-1, levels of which were measured in sera from 117 healthy controls, 58 patients with chronic pancreatitis, and 159 patients with pancreatic adenocarcinoma prior to treatment.

Although none of the biomarkers individually were highly correlated, a panel comprising 40 biomarkers “characterized individually by 32% sensitivity at 95% specificity would require any 7 biomarkers to be above the threshold and would result in a panel specificity and sensitivity of 99% each.” When correlation assumptions were added, sensitivity for the 40 biomarker panel was reduced to 94% at an average correlation of 0.05 and 84% at an average correlation of 0.15.

“The model provides a framework for maximizing biomarker sensitivities and minimizing biomarker correlation,” Dr. Firpo stated, with the key being the ability to account for disease heterogeneity. The next step is systematic identification of 40 to 50 biomarkers that have these characteristics—32% sensitivity and 95% specificity—or better, he concluded.