Reproducibility in urine peptidome profiling using MALDI-TOF.

MALDI-TOF profiling of low molecular weight peptides (peptidome) usage is limited due to the lack of reproducibility from the confounding inferences of sample preparation, data acquisition, and processing. We applied MALDI-TOF analysis to profile urine peptidome with the aims to: (i) compare centrifugal ultrafiltration and dialysis pretreatments, (ii) determine whether using signal LOD (sLOD), together with data normalization, may reduce MALDI-TOF variability. We also investigated the influence of peaks detection on reproducibility. Dialysis allowed to obtain better MALDI-TOF spectra than ultrafiltration. Within the 1000-4000 m/z range, we identified 120 and 129 peaks in intra- and interassay studies, respectively. To estimate the sLOD, serial dilution of pooled urines up to 1/256 were analyzed in triplicate. Six data normalization strategies were investigated-the mean, median, internal standard, relative intensity, TIC, and linear rescaling normalization. Normalization methods alone performed poorly in reducing features variability while when combined to sLOD adjustment showed an overall reduction in features CVs. Applying a feedback signal processing approach, after median normalization and sLOD adjustment, CVs were reduced from 103 to 26% and 113 to 25% for the intra- and interassay, respectively, and spectra became more comparable in terms of data dispersion.

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.