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Published on: January 19, 2019
Identification of proteins expressed differently among surgically resected stage I lung adenocarcinomas
Eun Sil Ha1, Seonyoung Choi, Kwang Ho In
1Division of Respiratory and Critical Care Medicine, Department of Internal Medicine, College of Medicine, Korea University, Seoul, Korea.
Rationale:
Among patients with surgically resected stage I lung adenocarcinoma, some succumb to early recurrence, while others survive for more than 5 years. Few markers to predict prognoses in these patients have been accepted. Recent advances in proteomic methodologies offer a unique chance to identify new candidate biomarkers. The aim of this study is to find differences in protein expression in resected lung cancer tissue of stage I adenocarcinoma from patients with no recurrence for more than 5 years and from those with early recurrence.
Methods:
Lung cancer tissues were obtained from 15 patients with pathologically confirmed stage I adenocarcinoma. The patients were divided into two groups, those with recurrence within 36 months (early recurrence group, n=9) and those that were disease-free for over 5 years (disease free group, n=6). Tissue proteins were separated by a two-dimensional electrophoresis long gel system (30 × 40 cm) with set ranges (3-10 NL) and examined by nano-LC-ESI-MS/MS. Western blot assays were performed to validate these proteins.
Results:
Twelve protein spots were up-regulated and 8 were down-regulated in the disease-free group as compared with the recurrence group. Of the 12 up-regulated proteins, haptoglubin, tau-tubulin kinase-2 (TTBK2), thymidine phosphorylase, annexin-1, PIN1, CAPG, and SEC23 were validated by Western blot. Among the 8 down-regulated proteins, serpinB6 and trangelin-2 were validated.
Conclusions:
A total of 9 differentially expressed proteins were successfully extracted, identified, and confirmed from stage I lung adenocarcinoma tissues. The increased or decreased expression of these proteins according to prognosis may be the basis for further studies of proteomics in developing prognostic biomarkers.