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

作者：Padoan Andrea; Seraglia Roberta; Basso Daniela; Fogar Paola; Sperti Cosimo; Moz Stefania; Greco Eliana; Marchet Alberto; de Manzoni Giovanni; Zambon Carlo Federico; Navaglia Filippo; Cristadoro Luigi; Di Chiara Alda; Nitti Donato; Pedrazzoli Sergio; Pavanello Girolamo; Plebani Mario^*

来源：Pancreas, 2013, 42(4): 622-632.

DOI：10.1097/MPA.0b013e318273096c

• pancreatic neoplasms
• diabetes mellitus
• apolipoprotein-A1
• complement C3
• gastric cancer
• mass spectrometry

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). %26lt;br%26gt;Methods: Sera were purified by Sep-Pak C18 before MALDI-TOF/MS Anchorchip analysis. %26lt;br%26gt;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. Tenfold cross-validation binary recursive partitioning trees were obtained for patients%26apos; 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. %26lt;br%26gt;Conclusions: The findings made demonstrate a role for serum peptides identified using MALDI-TOF/MS for addressing PaCa diagnosis.

• 出版日期2013-5