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. Copyright © 2013 Lippincott Williams & Wilkins.

Usefulness of MALDI-TOF/MS identification of low-MW fragments in sera for the differential diagnosis of pancreatic cancer

Seraglia R;
2013

Abstract

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. Copyright © 2013 Lippincott Williams & Wilkins.
2013
Istituto di Chimica della Materia Condensata e di Tecnologie per l'Energia - ICMATE
Istituto di Scienze e Tecnologie Molecolari - ISTM - Sede Milano
apolipoprotein-A1
complement C3
diabetes mellitus
gastric cancer
mass spectrometry
pancreatic neoplasms
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Descrizione: Usefulness of MALDI-TOF/MS Identification of Low-MW Fragments in Sera for the Differential Diagnosis of Pancreatic Cancer
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/275806
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