Serum peptide signatures for pancreatic cancer based on mass spectrometry: a comparison to CA19-9 levels and routine imaging techniques.

Purpose: The detection of pancreatic tumors lacks a sensitive and specific diagnostic tool. Mass spectrometry (MS)-based profiling of serum proteins is a promising approach for discovery of new clinical biomarkers or biomarker signatures.

Methods: Serum samples from pancreatic cancer (PC) patients and control individuals were collected and processed using a standardized protocol. Samples were divided in a calibration set (n = 49 PC and 110 controls) and a validation set (n = 39 PC and 75 controls). Peptide profiles were obtained using a combination of automated solid-phase extraction with reversed-phase C18 paramagnetic beads and matrix-assisted laser desorption ionization time-of-flight MS.

Results: Linear discriminant analysis with double cross-validation resulted in a discriminating peptide signature for PC in the calibration set with a sensitivity of 78 % and a specificity of 91 % [area under the curve (AUC) of 92 %]. Classification was validated with a sensitivity of 93 % and a specificity of 100 % (AUC of 98 %), and the results were compared with carbohydrate antigen 19-9 levels and currently available clinical imaging techniques. The ten most discriminating peptide peaks were identified as fragments of proteins involved in the clotting cascade, acute phase response and immunologic response.

Conclusions: In this study, it is shown that MS-based serum peptide profiles can discriminate between PC and control samples. The approach has great potential for high-throughput analysis in surveillance programs and appears to be most promising for patients with an inherited risk for PC, who benefit from more frequent screening.