58 Comprehensive Mass Spectrometry Based Metabolomic Profiling of Blood Plasma Reveals Potent Discriminatory Classifiers of Pancreatic Adenocarcinoma

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analysed by nanoLC mass spectrometry and MS/MS on an FT mass spectrometer. Peptides were identified using the Mascot software and an in-house mucin database. Primary diagnostic endpoints: 1) Surgical pathology (35%); 2) Follow-up with imaging (50%), mean followup time 11.3 months; 3) Preliminary diagnosis, based on all clinical data except proteomics' results (blinded) (15%). Results: 46 patients were enrolled (24 females; median age 64 years). Results for proteomics and cytology are available for all cases, whereas low cyst fluid yield precluded CEA analysis in 16 patients. The performance characteristics of proteomics for distinguishing (pre-) malignant PCL from constitutionally benign ones (serous cystic tumours, pseudocysts), were compared to corresponding results for CEA and cytology with mucus staining. Proteomic detection of any mucin except MUC6 (also observed in serous cystic tumours) was considered to indicate potential for malignancy. With this approach, the sensitivity, specificity and accuracy for proteomics were 97, 100 and 98% vs. 67, 80 and 73% for CEA (p=0.018/ns/0.002) and 57, 82 and 66% for cytology (p=0.0004/ns/ 0.00006). For the 16 cases with available surgical pathology, we separately compared cyst fluid MUC1 expression to cell atypia (cytology) as preoperative markers for overt malignancy (CIS/ invasive disease). Sensitivity, specificity and accuracy for MUC1 were 89, 86 and 88% vs. 22, 57 and 38% for cytology (p=0.015/ns/0.009). Conclusions: Proteomic evaluation of mucin expression was highly accurate in identifying (pre-) malignant PCL, comparing favourably with current standard cyst fluid analyses. MUC1 was significantly superior to cytology, in predicting overt malignancy. Minimal cyst fluid requirements for proteomics, also allowed for the analysis of lesions that, due to small size or viscous content, returned a low yield.

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