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Updated: Jul 2, 2026
A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions
Published on: April 18, 2025
Applying proteomic-based biomarker tools for the accurate diagnosis of pancreatic cancer
Kyoko Kojima1, Senait Asmellash, Christopher A Klug
1Department of Microbiology, University of Alabama at Birmingham, Birmingham, AL, USA.
Background:
The proteome varies with physiologic and disease states. Few studies have been reported that differentiate the proteome of those with pancreatic cancer.
Aim:
To apply proteomic-based technologies to body fluids. To differentiate pancreatic neoplasia from nonneoplastic pancreatic disease.
Methods:
Samples from 50 patients (15 healthy (H), 24 cancer (Ca), 11 chronic pancreatitis (CP)) were prospectively collected and underwent analysis. A high-throughput method, using high-affinity solid lipophilic extraction resins, enriched low molecular weight proteins for extraction with a high-speed 200-Hz matrix-assisted laser desorption/ionization time-of-flight mass spectrometer (MALDI-MS; Bruker Ultraflex III). Samples underwent software processing with FlexAnalysis, Clinprot, MatLab, and Statistica (baseline, align, and normalize spectra). Nonparametric pairwise statistics, multidimensional scaling, hierarchical analysis, and leave-one-out cross validation completed the analysis. Sensitivity (sn) and specificity (sp) of group comparisons were determined. Two top-down-directed protein identification approaches were combined with MALDI-MS and tandem mass spectrometry to fully characterize the most significant protein biomarker.
Results:
Using eight serum features, we differentiated Ca from H (sn 88%, sp 93%), Ca from CP (sn 88%, sp 30%), and Ca from both H and CP combined (sn 88%, sp 66%). In addition, nine features obtained from urine differentiated Ca from both H and CP combined with high efficiency (sn 90%, sp 90%). Interestingly, the plasma samples (considered by the Human Proteome Organization to be the preferred biological fluid) did not show significant differences. Multidimensional scaling indicated that markers from both serum and urine led to a highly effective clinical indicator of each specific disease state.
Conclusions:
The proteomic analysis of noninvasively acquired biological fluids provided a high level of predictability for diagnosing pancreatic cancer. While the proteomic analysis of serum was capable of screening individuals for pancreatic disease (i.e., CP and Ca vs. H), specific urine biomarkers further distinguished malignancy (Ca) from chronic inflammation (CP).
