Origin and Diagnostic Prospects of Tumor-Specific Serum Peptidome Patterns

抄録

Past studies have established distinctive serum peptidome patterns through mass spectrometry that seem to correlate with clinically relevant outcomes. Wider acceptance of these patterns as valid biomarkers for disease required characterization of the individual components and elucidation of the mechanisms by which they are generated. Using an automated, high-throughput peptide extraction and MALDI-TOF MS-based approach, we have shown that a limited subset of serum peptides provides class discrimination between patients with three different types of solid tumors and control individuals without cancer. Sequence analysis revealed that these peptides sort into a small number of clusters, and that most are generated by exopeptidase activities that confer cancer-type-specific differences superimposed on the proteolytic events of the ex-vivo coagulation and complement degradation pathways. Serum peptide profiling by MALDI-TOF MS thus monitors blood proteome metabolomic products and the observed peptides are only surrogates for the real biomarkers: exopeptidases, or better, exopeptidase activities. Our peptidome analysis platform is therefore particularly well suited for detection of cancer as proteases are established components of cancer progression and invasiveness. Building on these observations, we have developed quantitative blood-exopeptidase assays as a novel tool for cancer detection. The prototype test tracks degradation of artificial peptide substrates, under strictly controlled conditions, using the established automated extraction / MS-analysis method to monitor resulting patterns. Each fragment is quantitated by comparison with double-labeled, non-degradable internal standards (synsthesized of all-D-amino acids). The full array of metabolites ('mini-peptidome') is then subjected to multivariate statistical analysis. Using this approach, we have analyzed serum samples of cancer patients and healthy controls and obtained class predictions with 94% sensitivity and 90% specificity. The test effectively bypasses reproducibility problems related to sample collection, storage and handling, as well as with potential variability in endogenous peptide precursor levels. It may lead to a fundamentally new approach to biomarker development.