A Serum Biomarker Model to Diagnose Pancreatic Cancer Using Proteomic Fingerprint Technology

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Fig.1.
Representative spectra of a plasma sample in the range of 2,000 to 10,000 m/z obtained using SELDI-TOF-MS.
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Fig.2.
Differential expression of surface-enhanced laser desorption and ionization peak m/z 5705 in the comparison of pancreatic cancer (top 4) and control (bottom 4) sera. Profile shown in peak display (top) and gel view (bottom) mode (Biomarker Wizard 3.0).
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Fig.3. BPS decision tree model.
The decision tree detailed the decision-making procedure and sample distribution of the BPS model. Each square is a node, which was labeled by a node number. Blue frames represented parent nodes and red frames represented terminal nodes.
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Fig.4.
ROC curve of the decision tree model.

Table 2.

Important protein peaks that can be used for comparison of patients with pancreatic cancer and controls selected by BPS.

Peaks were named by their m/z.
↵* the most important peak was assigned an importance index of 100;
↵** these were the proteins that were selected to construct the decision tree model.