Abstract
Lung cancer is the leading cause of cancer deaths worldwide. Clinically, the treatment of non-small cell lung cancer (NSCLC) can be improved by the early detection and risk screening among population. To meet this need, here we describe the application of extensive peptide level fractionation coupled with label free quantitative proteomics for the discovery of potential serum biomarkers for lung cancer, and the usage of Tissue microarray analysis (TMA) and Multiple reaction monitoring (MRM) assays for the following up validations in the verification phase. Using these state-of-art, currently available clinical proteomic approaches, in the discovery phase we confidently identified 647 serum proteins, and 101 proteins showed a statistically significant association with NSCLC in our 18 discovery samples. This serum proteomic dataset allowed us to discern the differential patterns and abnormal biological processes in the lung cancer blood. Of these proteins, Alpha-1B-glycoprotein (A1BG) and Leucine-rich alpha-2-glycoprotein (LRG1), two plasma glycoproteins with previously unknown function were selected as examples for which TMA and MRM verification were performed in a large sample set consisting about 100 patients. We revealed that A1BG and LRG1 were overexpressed in both the blood level and tumor sections, which can be referred to separate lung cancer patients from healthy cases.
Highlights
Lung cancer is the most frequent cancer in the world, in terms of both incidence and mortality
Compared to a traditional one-dimensional RPLC separation, proteome coverage was improved, considering that more than three times as many proteins were identified by integrated multidimensional liquid chromatography (IMDL) under the same peptide-spectrum match (PSM) false discovery rate (FDR) criteria (Data not shown)
To further ascertain the performance of target-decoy strategy and its derived FDR, another widely used protein identification workflow, Trans-Proteomic Pipeline (TPP) [26], was applied to all the raw spectra coming from one healthy serum sample
Summary
Lung cancer is the most frequent cancer in the world, in terms of both incidence and mortality. Non-small cell lung cancer (NSCLC) accounts for 80–85% of lung cancer with an overall 5year survival rate less than 14% [1]. The 5-year survival rate is barely 3% to 7% for stage IIIB, and is less than 1% for stage IV disease [2]. Patients diagnosed at an early stage and have surgery experience an 86% overall 5-year survival [3]. New diagnostics are needed to detect early stage lung cancer because it may be cured with surgery. Several potential protein signatures such as carcinoembryonic antigen, CYFRA21-1, plasma kallikrein B1 and neuron-specific enolase have been discovered and clinically used as biomarker candidates for lung cancer. Biomarkers for early diagnosis of lung cancer are urgently needed
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