胰臟癌是一種高死亡率的癌症，在美國占癌症死因第四位，在台灣則是國人癌症死因第十位。由於胰臟癌在早期幾乎沒有顯著的病徵且對於現行醫療處置反應不佳，整體五年存活率小於5%。目前診斷胰臟癌主要是藉由影像檢查並輔以血液生物標誌CA19-9為參考，然而仍有靈敏性及專一性不足的問題，且對於早期胰臟癌的偵測並無特別顯著的效力。因此尋找並鑑定有效的胰臟癌血液生物標誌，是現今胰臟癌症預防醫學研究重視的課題之一。在本論文中，首先利用先前實驗室所建立的胰臟癌腫瘤細胞(PANC-1與MIA PaCa-2)分泌蛋白體與公開資料庫中胰臟癌組織轉錄體學研究資料進行整合性分析，找到30種蛋白質可以在此兩胰臟癌細胞株的分泌蛋白體中被偵測鑑定到，且在胰臟癌病人的組織轉錄體中有過量表現的情形。透過文獻資料參考及初步驗證，挑選其中4種蛋白質進一步驗證其做為有效的胰臟癌生物標誌之可能性。利用免疫組織染色分析，發現此4種蛋白質在胰臟癌病人組織中都有過量表現的情形，此結果與胰臟癌組織轉錄體學資料相符。而其中2種蛋白質在胰臟癌病人血液檢體中之含量相較於在健康對照組的血液檢體中有顯著的差異，顯示此2種蛋白質具有做為診斷胰臟癌之血清生物標誌的潛力。同時測量胰臟癌病人血清中的CA19-9含量，結果顯示此2種蛋白質在胰臟癌病人血清中的含量差異性，可以提高使用CA19-9做為胰臟癌臨床診斷的偵測效力。另一方面，針對其中之一個蛋白質-- endoplasmic reticulum oxidoreductin 1-like (ERO1L)在胰臟癌中所扮演的角色，本論文也建立了ERO1L 持續被抑制之胰臟癌腫瘤細胞株進行研究。利用以iTRAQ技術為基礎的蛋白質體定量方法系統性分析蛋白質在細胞培養液中與細胞體中含量的改變，進一步評估ERO1L在胰臟癌可能扮演的角色。經由整體性的分析，我發現當ERO1L持續被抑制時，相較於細胞體中所鑑定到的蛋白質，在細胞培養液中所鑑定到的蛋白質含量變化較顯著。此結果顯示ERO1L在胰臟癌中可能具有調控蛋白質分泌的功能。

Pancreatic cancer is the tenth leading cause of cancer death in Taiwan and the fourth in the United States. The five-year survival rate is less than 5% because of its late diagnosis and resistance to various treatments. Current diagnosis based on imaging or endoscope methods is very limited in early diagnosis. Even the usage serological tumor marker, CA19-9, also presents limited specificity and sensitivity. We propose to use an established cancer cell secretome database combined with efficiently analysis strategy to find out candidate proteins to be a potential pancreatic cancer marker for early detection or diagnosis. Two pancreatic cancer cell lines, PANC-1 and MIA PaCa-2 were used in pancreatic cancer cell secretome profiling. Integrated analysis strategy was performed to concentrate candidate proteins. With preliminary verification, four proteins presented highly potential as the detection markers for pancreatic cancer. Immunohistochemical analyses revealed elevated expressions of all four proteins in pancreatic cancer tissues compared with paired adjacent non-cancerous tissues (n = 31-67). The serum levels of two proteins among all pancreatic cancer patients (n = 154) and in early-stage cancer patients (n = 35-108) were significantly different with those in healthy controls (p < 0.0001). The combination of the two proteins and CA 19-9 outperformed each marker alone in distinguishing pancreatic cancer patients from healthy persons. These data revealed high potential of the two proteins as serological biomarkers for pancreatic cancer detection. Furthermore, an iTRAQ-based quantitative analysis was performed on one of the four proteins, endoplasmic reticulum oxidoreductin 1-like (ERO1L) knock-down cells to evaluate the role of ERO1L in pancreatic cancer. A comprehensive analysis showed that the amount of proteins identified in conditioned media was dramatically changed when ERO1L was knocked down in pancreatic cancer cells. This finding supports the role of ERO1L functions in regulation of protein secretion in pancreatic cancer cells.

Table of Contents
指導教授推薦書 ……………………………………………………………………
論文口試委員會審定書 ……………………………………………………………
授權書 ……………………………………………………………………………iii
誌謝 ………………………………………………………………………………vi
中文摘要 …………………………………………………………………………vii
英文摘要 …………………………………………………………………………ix
目錄 ………………………………………………………………………………xi
Chapter I Introduction
1.1 Incidence and classification of pancreatic cancer…1
1.2 Genetic and epigenetic alterations in pancreatic cancer ……………………………………………………………………………2
1.3 Risk factors associated with pancreatic cancer……3
1.4 Diagnosis of pancreatic cancer………………………………4
1.5 Serum biomarkers for pancreatic cancer detection…5
1.6 Approaches to discover cancer biomarkers………………8
1.7 ERO1L, a candidate pancreatic cancer biomarker identified in this thesis………………………………………………10
1.8 ERO1L-mediated protein secretion in human……………11
1.9 The role of ERO1L in cancer…………………………………13
1.10 Specific aims of this thesis………………………………14
Chapter II Materials and Methods
2.1 Patient population and clinical specimens……………15
2.2 Cell culture………………………………………………………15
2.3 Harvest of conditioned media (CM) and cell extracts (CE) from cell lines………………………………………………………16
2.4 Generation of secretome dataset of cancer cell lines………………………………………………………………………………17
2.5 Public domain database search for expression profiles of proteins identified in secretome dataset………18
2.6 Western blot analysis…………………………………………18
2.7 Immunohistochemistry (IHC)…………………………………19
2.8 Analysis of KLK7 and ULBP2 serum levels………………20
2.9 Analysis of BIGH3 and CA19-9 serum levels……………21
2.10 Establishment of ERO1L knock-down cell clones……22
2.11 iTRAQ-LC-MS/MS analysis………………………………………22
2.12 Prediction of protein secretion pathways……………26
2.13 Statistical analyses……………………………………………26
Chapter III Results
3.1 Analysis of the established pancreatic cancer cell secretome…………………………………………………………………………27
3.2 Integrated analyses of pancreatic cancer cell secretome…………………………………………………………………………27
3.3 Generation of candidate list (A) by integrating pancreatic cancer cell secretome with pancreatic cancer serum proteome…………………………………………………………………29
3.4 Generation of candidate list (B) by integrating pancreatic cancer cell secretome with cancer cell secretome database…………………………………………………………………………30
3.5 Generation of candidate list (C) by integrating pancreatic cancer cell secretome with pancreatic cancer tissue transcriptome………………………………………………………30
3.6 Verification of biomarker candidates in pancreatic cancer cell lines and tissue sections………………………………32
3.7 Overexpression of BIGH3, ERO1L, KLK7 and ULBP2 in pancreatic cancer tissues………………………………………………33
3.8 Serum levels of BIGH3, KLK7, and ULBP2 in pancreatic cancer patients………………………………………………34
3.9 The efficacy of KLK7, ULBP2 and CA 19-9 for screening pancreatic cancer……………………………………………35
3.10 The suitability of KLK7, ULBP2 and CA 19-9 for early detection of pancreatic cancers………………………………36
3.11 Blood ULBP2 levels in patients with other cancer types………………………………………………………………………………37
3.12 Establishment of the ERO1L knock-down cell clones from pancreatic cell line PANC-1……………………………………38
3.13 iTRAQ-LC-MS/MS analysis of protein expression in ERO1L knock-down and vector control cells………………………39
3.14 Data analysis of quantified proteins with iTRAQ ratio………………………………………………………………………………41
3.15 Identification of proteins differentially expressed in ERO1L knock-down cells………………………………………………42
Chapter IV Discussion
4.1 The secretome-based approach for biomarkers identification…………………………………………………………………45
4.2 Novel biomarkers for pancreatic cancer detection…46
4.3 A novel biomarker panel for pancreatic cancer detection…………………………………………………………………………47
4.4 BIGH3, one of novel biomarkers for pancreatic cancer detection………………………………………………………………48
4.5 KLK7, one of novel biomarkers for pancreatic cancer detection…………………………………………………………………………49
4.6 ULBP2, one of novel biomarkers for pancreatic cancer detection………………………………………………………………50
4.7 ERO1L, one of novel biomarkers for pancreatic cancer detection………………………………………………………………53
4.8 Conclusion…………………………………………………………55
References………………………………………………………………………56

 
List of Tables and Figures
Table
Table 1 Potential serological markers reported for pancreatic cancer……………………………………………………………72
Table 2 List of pancreatic cancer cell-secreted proteins that are presented in two candidate lists………………………75
Table 3 Proteins that are identified in pancreatic cancer cell secretome and upregulated in serum of pancreatic cancer patients………………………………………………………………76
Table 4 Proteins that are identified in pancreatic cancer cell secretome but not in other types of cancer secretome…………………………………………………………………………77
Table 5 Proteins that are identified in pancreatic cancer cell secretome and their genes are upregulated in pancreatic cancer tissues………………………………………………78
Table 6 Expression patterns of candidate proteins in cancer cell lines and cancer tissue on preliminary test……………80
Table 7 Correlation between clinicopathological features and BIGH3 expression in cancerous tissue from 31 pancreatic cancer patients………………………………………………………………81
Table 8 Correlation between clinicopathological features and ERO1L expression in cancerous tissue from 61 pancreatic cancer patients………………………………………………………………82
Table 9 Correlation between clinicopathological features and KLK7 expression in cancerous tissue from 35 pancreatic cancer patients………………………………………………………………83
Table 10 Correlation between clinicopathological features and ULBP2 expression in cancerous tissue from 67 pancreatic cancer patients………………………………………………84
Table 11 Correlation of serum BIGH3, ULBP2, KLK7, and CA19-9 with clinicopathologic characteristics in 154 pancreatic cancer patients………………………………………………85
Table 12 iTRAQ ratios and predicted secretion pathways of dysregulated proteins in conditioned media……86
Table 13 iTRAQ ratios and predicted secretion pathways of dysregulated proteins in cell extracts…………89

Figures
Figure 1 Workflow for candidate biomarkers identification, validation and further functional analysis in this thesis…………………………………………………………………95
Figure 2 Detection of 7 candidate proteins in pancreatic cancer cells and their conditioned media…………96
Figure 3 Detection of 7 candidate proteins in pancreatic cancer in pancreatic tissue sections………………97
Figure 4 Detection of BIGH3 expression in 31 pancreatic cancer tissues by IHC……………………………………99
Figure 5 Detection of ERO1L expression in 61 pancreatic cancer tissues by IHC……………………………………100
Figure 6 Detection of KLK7expression in 35 pancreatic cancer tissues by IHC……………………………………101
Figure 7 Detection of ULBP2 expression in 67 pancreatic cancer tissues by IHC……………………………………102
Figure 8 The degrees of differential expression with BIGH3, ERO1L, KLK7, and ULBP2…………………………………………103
Figure 9 Serum levels of BIGH3, KLK7, ULBP2, and CA 19-9 in pancreatic cancer patients…………………………………104
Figure 10 Correlations between KLK7, ULBP2 and CA 19-9……………………………………………………………………………………105
Figure 11 Receiver operating characteristic (ROC) curve analyses of BIGH3, KLK7, ULBP2, and CA 19-9 in pancreatic cancer patients……………………………………………107
Figure 12 Efficacy of KLK7, ULBP2, and CA 19-9 for early detection of pancreatic cancer………………………………108
Figure 13 ULBP2 levels in blood specimens from other cancer types…………………………………………………………………109
Figure 14 Result of ERO1L and ERO1L sequence alignment and ERO1L shRNAs targeting sequences………………110
Figure 15 Detection of ERO1L in shRNA transfected PANC-1 cells…………………………………………………………………111
Figure 16 The flow chart of iTRAQ-based quantitative proteomic analysis by 2D LC-MS/MS…………………………………112
Figure 17 Protein expression profiles of conditioned media and cell extracts in ERO1L knock-down experiment…113
Figure 18 Global distribution of quantified protein ratios……………………………………………………………………………114
Figure 19 Correlations of iTRAQ ratios and secretion profiles of dysregulated proteins in ERO1L knock-down experiment……………………………………………………………………115


 
Abbreviations
2D two-dimensional
ADAMs a disintegrin and metalloproteases
AUCs areas under the curves
BIGH3/TGFBI transforming growth factor-b-induced protein ig-h3
CA 19-9 carbohydrate antigen 19-9
CE cell extracts
CEA carcinoembryonic antigen
CGMH Chang Gung Memorial Hospital
CM conditioned media
CRC colorectal carcinoma
CT computed tomography
DMEM Dulbecco’s modified Eagle’s medium
emPAI exponentially modified protein abundance index
ER endoplasmic reticulum
ERO1L endoplasmic reticulum oxidoreductin 1-like
ERp44 endoplasmic reticulum protein 44
ETS1 v-ets erythroblastosis virus E26 oncogene homolog 1
EUS endoscopic ultrasound
FBS fetal bovine serum
GAPDH glyceraldehyde-3-phosphate dehydrogenase
GC gastric cancer
GEO Gene Expression Omnibus
HIF-1 hypoxia-inducible factor 1
HPA Human Protein Atlas database
HPLC high performance liquid chromatography
IGFBP7 insulin-like growth factor-binding protein 7
IHC immunihistochemistry
IPI International Protein Index
KLK7 kallikrein-7
LC-MS/MS liquid chromatography-tandem mass spectrometry
LTQ-Orbitrap linear trap quadrupole-Orbitrap
MMPs metalloproteases
NAPA a-soluble NSF attachment protein
NCBI National Center for Biotechnology Information
NK cell natural killer cell
NKG2DL Natural Killer group 2D ligand
NPC nasopharyngeal carcinoma
PBS phosphate-buffered saline
PC pancreatic cancer
PDAC pancreatic ductal adenocarcinoma
PDI protein disulfide isomerase
PGK1 phosphoglycerate kinase 1
PQD pulsed Q collision induced dissociation
PSAP prosaposin
ROC receiver operator characteristic
RT room temperature
SILAP stable isotope labeled proteome
TMHMM transmembrane Hidden Markov model
TNM tumor-node-metastasis
TPP Trans-Proteomics Pipeline
ULBP2 UL16 binding protein 2
UPR unfolded protein response
US ultrasound
VAPA vesicle-associated membrane protein-associated protein A
VEGF vascular endothelial growth factor

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