Investigating the use of novel blood processing methods to boost the identification of biomarkers of non-small cell lung cancer
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Background and objectives
Diagnosis of non-small cell lung cancer (NSCLC) currently relies on imaging and in-clinic visits, however these methods are not effective at detecting early-stage disease. The investigation into blood-based biomarkers aims to simplify the diagnostic process and has the potential for identifying disease-associated changes before they can be seen using imaging techniques.
Methods and design
In this study, plasma and frozen whole blood cell pellets from patients with NSCLC and healthy controls were processed using both classical as well as novel techniques to produce a unique set of 4 sample types from a single blood draw. Samples were analysed using 12 commercially available immunoassay kits in addition to liquid chromatography mass spectrometry using a Q Exactive HF-X Orbitrap to collectively screen 3974 proteins as potential biomarkers.
Results and conclusions
Analysis of all sample types produced a set of 522 differentially expressed proteins, with conventional blood analysis (proteomic analysis of plasma) accounting for only 7 of that total. Boosted regression tree analysis of the differentially expressed proteins produced a panel of 13 proteins that were able to discriminate between controls and NSCLC patients with an area under the ROC curve (AUC) of 0.864 for the set. Our rapid and reproducible blood preparation and analysis methods enable the production of high-quality data from small aliquots of complex samples that are typically seen as requiring significant fractionation prior to proteomic analysis.
