Usefulness of MALDI-TOF/MS Identification of Low-MW Fragments in Sera for the Differential Diagnosis of Pancreatic Cancer

Objectives To identify new biomarkers of pancreatic cancer (PaCa), we performed MALDI-TOF/MS analysis of sera from 22 controls, 51 PaCa, 37 chronic pancreatitis, 24 type II diabetes mellitus (DM), 29 gastric cancer (GC), and 24 chronic gastritis (CG). Methods Sera were purified by Sep-Pak C18 before MALDI-TOF/MS Anchorchip analysis. Results Features present in at least 5% of all spectra were selected (n = 160, m/z range, 1200–5000). At univariate analysis, 2 features (m/z 2049 and 2305) correlated with PaCa, 3 (m/z 1449, 1605, and 2006) with DM. No feature characterized gastric cancer or chronic gastritis. Ten-fold cross-validation binary recursive partitioning trees were obtained for patients’ classification. The tree (CA 19-9, age, m/z 2006, 2599, 2753, and 4997), built considering only patients with diabetes, allowed a distinction between DM [area under the receiver operating characteristic curve (AUC), 0.997], chronic pancreatitis (AUC, 0.968), and PaCa (AUC, 0.980), with an overall correct classification rate of 89%. The tree including CA 19-9, 1550, and 2937 m/z features, achieved an AUC of 0.970 in distinguishing localized from advanced PaCa. MALDI-TOF-TOF analysis revealed the 1550 feature as a fragment of Apo-A1, which was determined as whole protein and demonstrated to be closely correlated with PaCa. Conclusions The findings made demonstrate a role for serum peptides identified using MALDI-TOF/MS for addressing PaCa diagnosis.