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There are no satisfactory plasma biomarkers which are available for the early detection and monitoring of lung cancer, one of the most frequent cancers worldwide. The aim of this study is to explore the application of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-ToF MS) to plasma proteomic patterns to distinguish lung cancer patients from healthy individuals. The EDTA plasma samples have been pre-fractionated using magnetic bead kits functionalized with weak cation exchange coatings. We compiled MS protein profiles for 90 patients with squamous cell carcinomas (SCC) and compared them with profiles from 187 healthy controls. The MALDI-ToF spectra were analyzed statistically using ClinProTools bioinformatics software. Depending on the sample used, up to 441 peaks/spectrum could be detected in a mass range of 1000-20,000 Da; 33 of these proteins had statistically differential expression levels between SCC and control plasma (P < 0.001). The series of the peaks were automatically chosen as potential biomarker patterns in the training set. They allowed the discrimination of plasma samples from healthy control and samples from SCC patients (sensitivity and specificity >90%) in external validation test. These results suggest that plasma MALDI-ToF MS protein profiling can distinguish patients with SCC and also from healthy individuals with relatively high sensitivity and specificity and that MALDI- ToF MS is a potential tool for the screening of lung cancer.

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Blood plasma proteomes obtained from 77 lung squamous cell carcinoma (LSCC) patients (Stages I-III) and 67 healthy controls (all males) were analyzed by using the label-free liquid chromatography tandem mass spectrometry (LC-MS/MS) method for the search of potential cancer biomarkers. All plasma samples were depleted of 14 highly-abundant plasma proteins by immune-affinity column chromatography before LC-MS/MS. We identified and quantified 809 differential proteins with molecular weights from 6.4 kDa to 3900 kDa using a label-free method. Three hundred and sixty four proteins were identified in all three groups. Changes in levels of an expression of blood plasma proteins associated with LSCC were discovered. Among them, 43 proteins were overexpressed and 39 proteins were down-regulated by more than two-fold between the plasmas of lung cancer patients and healthy men. We focused our attention on proteins whose expression levels increased from control to early stage and then to advanced stage tumor. Each of the 43 unique overexpressed proteins was classified according to its cellular localization, biological processes, molecular function and classes. Many of these proteins are involved in biological pathways pertinent to tumor progression and metastasis and some of these deregulated proteins may be useful clinical markers.

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A label-free nano-liquid chromatography tandem mass spectrometry proteomics analysis on the conditioned media (CM) of two lung cancer cell lines of different histological backgrounds to identify secreted or membrane-bound proteins as novel lung cancer biomarkers was performed. Five hundred and seventy seven proteins were identified and 38% of them were classified as extracellular or membrane-bound. For the search of potential biomarkers of lung cancer a series of selection criteria were proposed. We detected known or putative lung cancer markers. In addition, 40 novel proteins were identified, whose role as biomarkers of lung cancer should be explored further.