Protein Expression and Glycosylation Level Change Associated Pancreatic Cancer.

Abstract

The discovery of molecular markers that distinguish certain diseases has improved the sensitivity and accuracy of diagnosis and contributed to the development of new therapeutic targets. Pancreatic cancer, as the most deadly cancer, has been studied by numbers of groups over the world to find molecular solutions to overcome the difficulties in diagnosing and curing this disease. The projects included in this dissertation are focused on obtaining such protein markers from serum or cancer tissue stem cells using innovative proteomic techniques. In the first two chapters, microarray/bead-based glycoprotein screening methods are developed to validate glycoprotein biomarkers with altered glycosylation structure in pancreatic cancer. The high-density microarray and multiplexed bead assays enabled the analysis of multiple biomarker candidates in hundreds of serum samples in a high-through-put manner. The binding affinity of A1BG with lectin SNA was found to effectively discriminate pancreatic cancer patients. Pancreatic cancer stem cells are studied by using CIEF-LC-MS/MS in the third projects depicted in Chapter Three. Cancer stem cells are responsible for the initiation and regeneration of tumors after therapy. However, studying the proteome of cancer stem cells were prohibited by the extremely small amount of cells that only make up to 1% of the whole tumor. We optimized a protocol of sample handling and a high-resolution first dimension separation to achieve the largest number of proteins identified with such amount of sample. The last chapter described a study of pancreatic cancer auto-antibody. Autoantibodies are generated from auto-immnune response against tumor specific antigens and thus can be used as biomarker. A certain type of autoantibody usually does not exist in the serum of every case but only a subset of the whole population with cancer. Therefore, after using microarray to screen the reactive fractions, a statistic method which catches biomarker with outlier pattern was used in our study instead of the regular T-test or Wilcoxson Ranking test. Anti-PGK was found to be significantly up-regulated in 20 percent of the cancer patient.