Identification of potential lung cancer biomarkers using an in vitro carcinogenesis model
Open Access
- 1 January 2008
- journal article
- Published by Springer Nature in Experimental & Molecular Medicine
- Vol. 40 (6), 709-20
- https://doi.org/10.3858/emm.2008.40.6.709
Abstract
Lung cancer is one of the deadliest and commonly diagnosed neoplasms. Early diagnosis of this disease is critical for improving clinical outcome and prognosis. Because the early stages of lung cancer often produce no symptoms, it is necessary to identify biomarkers for early detection, prognostic evaluation, and recurrence monitoring of the cancer. To identify potential lung cancer biomarkers, we analyzed the differential protein secretion from transformed bronchial epithelial cells (1198 and 1170-I) as compared to immortalized normal bronchial epithelial cells (BEAS-2B) and non-transformed cells (1799) all of which are derived from BEAS-2B and represent multistage bronchial epithelial carcinogenesis. The proteins recovered from the conditioned media of the cells were separated on two-dimensional gels. There was little difference between the secretome of the BEAS-2B and 1799 cells, whereas the patterns between the transformed 1198 and 1170-I cells and non-transformed 1799 cells were significantly different. Using mass spectrometry and database search, we identified 20 proteins including protein gene product 9.5 (PGP9.5), translationally controlled tumor protein (TCTP), tissue inhibitors of metalloproteinases-2 (TIMP-2), and triosephosphate isomerase (TPI), that were either increased or decreased simultaneously in conditioned media of both 1198 and 1170-I cells. Furthermore, levels of PGP9.5, TCTP, TIMP-2, and TPI were significantly increased not only in the conditioned media of both transformed cell lines when compared to those of BEAS-2B and 1799 cells, but also in plasmas and tissues from lung cancer patients when compared to those in normal controls. We suggest the PGP9.5, TCTP, TIMP-2, and TPI as promising candidates for lung cancer serum biomarkers.Keywords
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