| Summary: | 碩士 === 國立陽明大學 === 醫學生物技術暨檢驗學系暨研究所 === 98 === Lung cancer has been recognized as a common and dreadful cancer in the world but there is still no biomarker for the diagnosis, staging, or monitoring of this cancer disease. Among the FDA approved cancer serum markers, we noticed the markers themselves are either secreted or membrane proteins. Thus the identification of differentially expressed secreted proteins has the potential of discovering lung cancer biomarker candidates. In addition, since hypoxia has known to play an important role in the early phase of tumor progression. The identification of lung cancer hypoxia-related secreted proteins is another important project of my thesis works. In my study, I applied mass spectrometry, a robust high-throughput technology, to analyze the proteins in complex mixtures of lung secreted proteomes. To facilitate the identification of lung cancer biomarkers and hypoxia-related proteins, I integratively analyzed the proteomics data with public transcriptomics data. In my study, I used five lung cancer cell lines of different histological types to reduce the potential variations came from the different genetic backgrounds and to access the more complete disease proteomes. Approximately 309 (13,161 peptides) secreted and 601 (13,307 peptides) total cell lysate proteins of five lung cancer cell lines as well as 300 (5,846 peptides) hypoxic secreted proteins and 284 (5,206 peptides) normoxic secreted proteins were identified by LC-MS/MS. To acquire a list of candidates, the expression profiles of these proteins were analyzed with the publicly available transcriptomic datasets (Lung cancer microarray) and consolidated public secretome databases to find reliable secreted and differentially expressed protein candidates. As examples, PCSK1N, a potential cancer biomarker and also the hypoxia-related COL1A1, NID1, and GALNT2 were revealed in this study.
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