Investigating\nthe Use of Novel Blood Processing Methods\nto Boost the Identification of Biomarkers for Non-Small Cell Lung\nCancer: A Proof of Concept

Diagnosis of non-small cell lung cancer (NSCLC) currently\nrelies\non imaging; however, these methods are not effective for detecting\nearly stage disease. Investigating blood-based protein biomarkers\naims to simplify the diagnostic process and identify disease-associated\nchanges before they can be seen by using imaging techniques. In this\nstudy, plasma and frozen whole blood cell pellets from NSCLC patients\nand healthy controls were processed using both classical and novel\ntechniques to produce a unique set of four sample types from a single\nblood draw. These samples were analyzed using 12 immunoassays and\nliquid chromatography–mass spectrometry to collectively screen\n3974 proteins. Analysis of all fractions produced a set of 522 differentially\nexpressed proteins, with conventional blood analysis (proteomic analysis\nof plasma) accounting for only 7 of the total. Boosted regression\ntree analysis of the differentially expressed proteins produced a\npanel of 13 proteins that were able to discriminate between controls\nand NSCLC patients, with an area under the ROC curve (AUC) of 0.864\nfor the set. Our rapid and reproducible (<10% CV for technical\nreplicates) blood preparation and analysis methods enabled the production\nof high-quality data from only 30 μL of complex samples that\ntypically require significant fractionation prior to proteomic analysis.\nWith our methods, almost 4000 proteins were identified from a single\nfraction over a 62.5 min gradient by LC-MS/MS.