神經母細胞瘤是兒童最常見的顱外腫瘤，主要是由交感神經系統細胞在胚胎發育過程中發生突變而形成惡性腫瘤，神經母細胞瘤在台灣地區兒童癌症發生率僅次於白血病及淋巴瘤，但其成因仍尚未釐清，且往往在診斷出疾病時，將近百分之八十的病童都已有轉移的現象，所以此疾病的早期診斷與治癒率有著密不可分的關係。另一方面，「缺氧現象」在固態腫瘤形成初期扮演著舉足輕重的角色，近兩年文獻指出，缺氧環境會使神經母細胞瘤細胞不再分化且會逐漸產生一些幹細胞的特徵，而走向較為不成熟的方向發展，使得整個腫瘤發展更為嚴重而難治癒。即便現今醫學已十分發達，但神經母細胞瘤治癒率與死亡率仍不樂觀，故尋找神經母細胞瘤的生物標記及藥物標的具有其迫切性和必要性。本論文中將使用高通量蛋白質體之比較分析方法來針對神經母細胞瘤細胞對缺氧的反應及癌症轉移相關蛋白進行系統化分析，藉此找尋與鑑定出與缺氧及轉移之相關蛋白，希望能藉此前瞻性的策略加速尋找神經母細胞瘤相關的治療標靶及生物標記，而間接增加此疾病的治癒率。本研究共使用三株神經母細胞瘤細胞株：SH-SY5Y、SK-N-BE(2)及IMR-32，前兩者用於鑑定缺氧相關蛋白，而後兩者的蛋白質體比較則用於鑑定癌症轉移相關蛋白。在鑑定缺氧相關蛋白部分，透過建立細胞代謝性穩定同位素標定技術 (SILAC) 及液相層析儀搭配串聯式液相質譜儀分析後，分別於SH-SY5Y及SK-N-BE(2)細胞的條件培養基中(conditioned media)鑑定出228 (6,862條胜肽鏈)，286 (9,601條胜肽鏈) 個蛋白質。同樣地於細胞溶解液(cell lysate)中鑑定出共338(9,154 胜肽鏈)及374(9,603 胜肽鏈) 個穩定同位素標定蛋白質。為了找尋較可信的候選蛋白，我們將缺氧環境中顯著表現兩倍以上的蛋白與神經母細胞瘤臨床樣本的微陣列資料和自行建立的分泌性蛋白及膜蛋白資料庫做整合性分析，最後得到數個候選蛋白，其中包括FN1 (fibronectin 1) 及MMP2 (matrix metalloproteinase 2) 兩個與缺氧具高度相關性的蛋白質。

在鑑定轉移相關蛋白部分，分別於IMR-32和SK-N-BE(2)的條件培養基中鑑定出340 (8,699條胜肽鏈) 及 377 (9,507條胜肽鏈) 個無同位素標定蛋白，同樣地，在IMR-32和SK-N-BE(2)的細胞溶解液中鑑定出421 (10,291條胜肽鏈) 和362 (11,018條胜肽鏈) 個無同位素標定蛋白質。同樣地，為了縮小尋找範圍及加速鑑定速度，將蛋白質體資料與前述的臨床樣本微陣列資料及本實驗室自行建立之資料庫做一系統性整合後，得到了幾個相當具有治療及診斷潛力癌症轉移相關蛋白質，如：VCAN (versican) 和L1CAM (L1 cell adhesion molecule)。無論在缺氧反應還是癌症轉移計劃，這些篩選出來的候選蛋白絕大部分都尚未有文獻指出和神經母細胞瘤有直接相關，甚至有些蛋白仍未指出與癌症相關，顯示本文研究結果在神經母細胞瘤研究領域中仍具有高度新穎性及發展性。本篇研究中我們使用了蛋白質體學研究策略，藉此鑑定缺氧環境下誘導出的蛋白質及癌症轉移之相關蛋白質，最終篩選出這些極具潛力的候選蛋白，期望有朝一日能應用在神經母細胞瘤治療上、臨床診斷或預後指標。

Neuroblastoma (NB) is the most common malignant solid tumor with unfortunate outcomes in many infants and children. This tumor arises from the sympathetic nervous system. The primary non-metastatic NB initiates at a localized area and is often resectable with good prognosis, but once metastasized, it is unresectable and resistant to chemotherapy while restraining tumor spread. The major type of NBs is the aggressive metastatic tumor. Furthermore, solid tumor cells have to overcome hypoxia and deficiency of nutrient. To ensure a sufficient supply of oxygen and nutrients, tumor metastasis or angiogenesis is probably a strategy for tumor growing in hypoxia. Therefore, the searching of differentially expressed hypoxia-induced and metastasis-related proteins, which are the aims of my thesis works, are important for the development of therapeutic target or diagnostic biomarker. The first project applied SILAC–based quantitative proteomics approach analyze hypoxia-induced protein in the secretome and cell lysate proteomes of NB cell lines, SH-SY5Y and SK-N-BE(2), cultured in hypoxia or normoxia condition. A total of 228 (6,862 peptides) and 286 (9,601 peptides) SILAC-labeled proteins were identified by LC-MS/MS in the secretomes of SH-SY5Y and SK-N-BE(2) cells, respectively, and 338 (9,154 peptides) and 374 (9,603 peptides) SILAC-labeled proteins in the cell lysates of SH-SY5Y and SK-N-BE(2) cells, respectively. These proteins were further analyzed with the public NV microarray data, in-house consolidated secretome databases, and membrane protein database to narrow down the hypoxia related candidates. In my study, a number of novel hypoxia-related candidates including FN1 (fibronectin 1) and MMP2 (matrix metalloproteinase 2) were identified.

The second project used a label-free quantitative proteomics approach to identify metastasis-related candidates by comparing the proteomes of metastatic and non-metastatic NB cell lines, SK-N-BE(2) and IMR-32, respectively. A total of 340 (8,699 peptides) and 377 (9,507 peptides) human proteins were identified in the conditioned media from IMR-32 and SK-N-BE(2) cells, respectively. Approximately 421 (10,291 peptides) and 362 (11,018 peptides) proteins were detected in the cell lysates of IMR-32 and SK-N-BE(2), respectively. To obtain the ideal candidates, the significantly changed proteins were integratively analyzed with public transcriptomic data and secretome and membrane protein databases. This analysis found several potential metastasis candidates including VCAN (versican) and L1CAM (L1 cell adhesion molecule) and many novel neuroblastoma metastasis protein candidates. In this study, we demonstrated the efficiency of our proteomics approach in the identification of hypoxia-induced and metastasis-related candidates which may deserve further investigations to evaluate their potential as neuroblastoma therapeutic targets, diagnostic or prognostic markers

CHINESE ABSTRACT I

ABSTRACT III

CONTENTS V

LIST OF TABLES VIII

LIST OF FIGURES X

ABBREVIATIONS XII

CHAPTER 1 INTRODUCTION 1

1.1 NEUROBLASTOMA 1

1.1.1 Clinical features of neuroblastoma 1

1.1.2 Metastasis of neuroblastoma 2

1.2 HYPOXIA RESPONSE 3

1.2.1 Molecular mechanism involved in hypoxia response 3

1.2.2 Hypoxia response in neuroblastoma 4

1.3 SPECIFIC AIM 5

CHAPTER 2 MATERIALS AND METHODS 6

2.1 CELL LINES, MEDIA, AND CULTURE CONDITIONS 6

2.2 STABLE ISOTOPE LABELING WITH AMINO ACIDS IN CELL CULTURE AND HYPOXIA TREATMENT 7

2.3 PREPARATION OF SECRETED PROTEOMES 1

2.4 PREPARATION OF CELL EXTRACTS 1

2.5 MEASUREMENT OF TOTAL PROTEIN CONCENTRATION 2

2.6 SDS-PAGE AND WESTERN BLOT ANALYSIS 1

2.7 TRYPSIN DIGESTION OF PROTEIN SAMPLES 2

2.8 PURIFICATION OF TRYPTIC PEPTIDE SAMPLES 1

2.9 MASS SPECTROMETRY 1

2.10 DATABASE SEARCHING OF TANDEM MASS DATA 2

2.11 STATISTICAL ANALYSIS OF PEPTIDE AND PROTEIN IDENTIFICATIONS 1

CHAPTER 3 RESULTS 2

3.1 QUALITY ASSESSMENT OF SUBPROTEOMES 2

3.2 EVALUATION OF HYPOXIA TREATMENT 3

3.3 SILAC-BASED QUANTITATIVE PROTEOMIC ANALYSIS OF NEUROBLASTOMA CELLS UNDER HYPOXIA VERSUS NORMOXIA 4

3.3.1 Identification of SILAC-labeled proteins using mass spectrometry 4

3.3.2 Quantitative analysis of SILAC-labeled proteins with MaXIC-Q software 5

3.3.3 Evaluations of the relationships between the hypoxia-related candidates with STRING functional interaction database analysis 6

3.4 ANALYSIS OF METASTATIC VERSUS NON-METASTATIC NEUROBLASTOMA CELL PROTEINS USING LABEL-FREE QUANTITATIVE PROTEOMIC APPROACH 8

3.4.1 Identification of label-free proteins using mass spectrometry 8

3.4.2 Subcellular localization and distribution of the identified proteins from subproteomes 9

3.4.3 Integrative analysis of neuroblastoma proteomics, microarray data, and in-house consolidated secretome and membrane proteome databases 10

3.4.3.1 Identification of neuroblastoma differentially expressed genes from public microarray data 10

3.4.3.2 Construction of in-house consolidated secretome database 11

3.4.3.3 Construction of in-house membrane proteome database 12

3.4.4 Evaluations of metastasis-related candidates with STRING protein-protein interaction database 12

3.4.5 Disease association analysis of metastatic versus non-metastatic NB cells differentially expressed proteins candidates 14

CHAPTER 4 DISCUSSION 15

TABLES 19

FIGURES 38

APPENDICES 56

REFERENCES 58

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