Abstract
e22146 Background: Radiation-induced lung toxicity (RILT) is dose limiting in the treatment of non small cell lung cancer (NSCLC). Early prediction of RILT would allow physicians to individualize treatment. This work aims to study if radiation induces differential changes in plasma proteomics in patients with and without RILT. Methods: 20 Patients with NSCLC in 3 stage- matched groups and treated with radiation therapy (RT) or chemoradiation were included in this analysis: 6 grade 0 (group 0), 8 grade 1 (group 1), and 6 grade ≥ 2 RILT (group 2). Platelet poor plasma was obtained pre-RT, at 2-, 4-, 6-week during-RT, and 1-, 3-month post-RT. The plasma proteomic characterizations from patients with and without RILT were compared using a multiplexed quantitative proteomics approach involving ExacTag labeling, reverse-phase high-performance liquid chromatography (RP-HPLC), and nano-LC electrospray tandem mass spectrometry (LC-ESI-MS/MS). ANOVA model was applied for significance test. Results: 23 common proteins were detected in all 20 patients, 9 of them, Ceruloplasmin, Prothrombin, Complement C3, Beta-2-glycoprotein (β2GP1) 1, Vitronectin, Complement factor I, Complement factor H, Complement C4-A, Complement C7, had significant difference among 3 groups. At baseline (Pre-RT), the levels of Vitronectin and C4-A in group 2 were both significantly higher than that in group 0 (p=0.008 and 0.021, respectively). At 2-week during RT, the levels of Ceruloplasmin, Prothrombin and β2GP1 in group 1 were significantly higher than that in group 0 (p=0.017, 0.011 and 0.013, respectively). At 4-week during RT, the levels of β2GP1 in group 1 and group 2 were significantly higher than that in group 0 (p=0.005 and 0.014). At 6-weeks during RT, Prothrombin, C3, Complement factor H, C7 and Complement factor I also had some significant changes among three groups. Conclusions: Plasma proteins related to inflammation, coagulation and fibrosis, such as β2GP1, change differently during RT in patients with and without RILT. This proteomic approach may identify new markers during treatment to predict RILT for adapting treatment to patient. Fundings: ASCO career developmental award, grant from Pardee foundation, and RTOG translational research program. No significant financial relationships to disclose.
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