Protein Signatures and Tissue Diagnosis of Pancreatic Cancer

Abstract Background Endoscopic ultrasound-guided fine needle aspiration (EUS-guided FNA) fails to diagnose up to 25% of patients with pancreatic ductal adenocarcinoma (PDAC). Proteomics may help to overcome this clinical dilemma. We hypothesized that soluble protein signatures can differentiate PDAC from benign tissues. Study Design Tissues were obtained from resected surgical specimens, lysed, and homogenates collected for analysis with a 41-protein multiplex assay. Analyte concentrations were normalized to total protein. Statistical analysis was performed to evaluate for differences in PDAC vs benign tissue. Results Tissues were obtained from 159 patients, 82 patients with PDAC naive to therapy and 77 with benign pancreatic pathology. Fourteen analytes had a receiver operating characteristic (ROC) curve area of >0.75 for predicting PDAC vs benign tissue. A recursive partitioning model using only two analytes, IL-1RA and TGFα, provided an accuracy, sensitivity, and specificity of 91.2%, 90.2%, and 92.2%, respectively. A penalized logistic regression model found 12 analytes that provide diagnostic value to a protein signature. The average area under the ROC after 50 10-fold cross validations was 0.951. Accuracy, sensitivity, and specificity of this model were 91.2%, 87.8%, and 94.8%, respectively. Applying the scenario of 80% disease prevalence in patients undergoing EUS with FNA for a pancreatic head mass, positive predictive value is 98.5% (95% CI 93.0%-99.7%) and negative predictive value is 66.0% (95% CI 54.9%-75.6%). Conclusion Protein signatures from pancreatic specimens can differentiate PDAC from benign tissue. Further work to validate these findings in a unique sample set is warranted.