Identification of Reliable Biomarkers for Radiation Pneumonia Using a Proteomics Approach

Abstract

Objective: The differences in the expression levels of differentially-expressed proteins (DEPs) in serum specimens from non-small cell lung cancer (NSCLC) patients presenting with radiation pneumonia (RP) and non-pneumonia at 0, 3, and 6 weeks after radiotherapy were compared by a quantitative proteomics approach. This study aims to identify reliable biomarkers for predicting RP. Methods: Twenty-eight patients who were pathologically diagnosed as locally advanced NSCLC and received radiotherapy for the first time from October 2017 to July 2018 were recruited. Serum samples were collected before radiotherapy and 3 and 6 weeks after radiotherapy. Three patients with grade ≥2 RP were assigned into the experimental group (RP group). Three patients with the same sex, pathological type, age, and clinical stage were selected from the remaining 25 patients without RP, and allocated into the control group (C group). DEPs were identified using tandem mass tags (TMT) labeling and liquid chromatography-mass spectrometry, functional annotation, functional enrichment, and protein-protein interaction (PPI) network analyses. Results: 812 quantifiable proteins were identified by mass spectrometry of peptides. Bioinformatics analysis revealed that these proteins were mainly involved in binding, biological regulation, metabolic processes, signaling transduction processes, and pertussis in the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway. Using 1.2 times as the threshold for differential expression change and p < 0.05 as the significance threshold, the expression levels of recombinant zyxin (ZYX) and recombinant fetuin B (FETUB) were up-regulated before radiotherapy and 3 weeks after radiotherapy (both p < 0.05). Recombinant Cystatin A (CSTA) and calmodulin-like 5 (CALML5) expression levels were down-regulated before radiotherapy and 6 weeks after radiotherapy (both p < 0.05). Nicotinamide nucleotide transhydrogenase (NNT) expression level was significantly down-regulated before radiotherapy and 3 and 6 weeks after radiotherapy, with ratios of 0.296, 0.314 and 0.238, respectively (all p < 0.05). The expression levels of NNT, haptoglobin-related protein (HPR), and pregnancy zone protein (PZP) were significantly down-regulated before radiotherapy, with ratios of 0.296, 0.377 and 0.376, respectively (all p < 0.05). PPI network constructed by STRING database found that fetuin B (FETUB) interacted with PZP among these DEPs, and PZP was associated with the pathophysiological pathways of RP, such as transforming growth factor-β (TGF-β), interleukin-1β (IL-1β), IL-6, tumor necrosis factor (TNF) and inflammatory response-related pathways. Conclusions: Quantitative proteomics analysis identifies the differences in the expression levels of DEPs between NSCLC patients presenting with or without RP throughout radiotherapy. Based on proteomics analysis and PPI network, FETUB and PZP are optimal candidate proteins for RP, which provides evidence for verifying the potential predictive biomarkers of RP.