Sun et al. (2016) present a biomarker discovery study that searches for serum proteins as indicators of altered metabolic function in patients with lung cancer.1 Their method includes protein elution plate (PEP) technology, with mass spectrometric (MS) proteomic analysis for identification.
One of the pathophysiological mechanisms employed by cancer cells is a shift on cellular metabolism that favors their survival over normal tissue. Cells respond to this change in pathways by creating different levels of metabolic enzymes. Sun et al. propose that clinicians might detect this shift in metabolism as biomarkers circulating in blood. Furthermore, they propose that looking for these types of biomarkers might provide an early diagnostic advantage in lung cancer since patients with this disease frequently overlook symptoms and present in later, less treatable stages for diagnosis. They also suggest that biomarker evidence of a metabolic shift could discriminate false positives arising from diagnostic imaging, and thus prevent invasive testing for a number of patients.
Sun et al. obtained serum samples from patients with confirmed lung cancer and used samples from healthy controls for comparison. Since the presence of highly abundant proteins influences MS-based proteomic evaluation, the team conducted enrichment/depletion using a commercial bead-based protocol that increases low-abundance proteins and depletes albumin prior to sample preparation. The team then used isoelectric focusing to separate proteins in the samples. Next, the preparations underwent a refolding step to restore protein tertiary structure before two-dimensional gel electrophoresis, followed by transfer onto a PEP plate.
Once transferred, the fractions underwent an enzyme function assay, looking at glycolytic pathway activity. When the researchers found differences in activity, they identified proteins involved by proteomic analysis using nano liquid chromatography–tandem mass spectrometry (nLC-MS/MS). Following in-gel trypsin digestion, Sun et al. separated the samples through an UltiMate RSLC system coupled with an LTQ Orbitrap Velos mass spectrometer (both Thermo Scientific).
Enrichment resulted in a 10-fold increase in enzyme assay sensitivity in addition to improved detection of low-abundance proteins. The researchers also found that modifications to the gel electrophoresis steps and additional protein refolding steps, such as reducing sodium dodecyl sulfate concentration and replenishing metals ions, ensured restoration of protein functionality for the enzyme activity assays. They also note that narrowing the substrate panel improved assay activity for measuring enzyme function.
From the enzyme assays, the research team found differential hexokinase activity in lung cancer patient serum compared with healthy controls, in some instances as much as 10-fold. Furthermore, following LC-MS/MS identification they found a wider range of proteins involved in this activity than expected, suggesting that this indicates a degree of multi-functionality.
In conclusion, Sun et al. are satisfied that the PEP workflow in addition to sample enrichment/depletion represents a valuable tool for biomarker discovery. Describing the approach as an “alternative and complementary approach to sequence annotation,” they suggest that functional proteomics shows potential for biomarker discovery, drug targeting and development of diagnostic kits in the future.
1. Sun, Z., et al. (2016) “Identification of functional metabolic biomarkers from lung cancer patient serum using PEP technology,” Biomarker Research, 4(11), doi: 10.1186/s40364-016-0065-4.