卵巢癌由於其早期症狀不明確，為全球女性中最致命的婦科癌症。由於該癌症在初期缺乏明顯的症狀，目前臨床醫學上仍缺乏針對一般風險女性有效的篩檢方法。近年研究中，胞外泌體中所包含的小分子核糖核酸已成為一個有潛力的卵巢癌生物標誌物，其表現量已被證實能反映卵巢癌的發生。此研究提出了一個整合型微流體系統，其可以自動化執行以小分子核糖核酸為分析物的液態活體切片試驗。此晶片具有將實驗步驟自動化執行能力，實驗步驟包括（一）萃取及分解胞外泌體，（二）萃取及定量小分子核糖核酸。此研究中，血漿中胞外泌體的萃取率為約52%，與先前所發表之54%相近並減少37.5%的操作時間，這歸因於同時使用了CD63 抗體磁珠和上皮細胞黏合分子之抗體磁珠 。此外，本研究提出了同時診斷兩種小分子核糖核酸目標物（即 miR-21 和 miR-200a）的檢測方法，該方法建立於多套式聚合酶連鎖反應的基礎之上。相較使用單一miR-21 檢測，這樣的多重檢測有助於提高卵巢癌診斷的靈敏度和特異性。此研究中，多套式聚合酶連鎖反應所衍生的校準曲線表現出高度線性，且沒有檢測到假陽性信號，因此該校準曲線可作為檢測 miR-21/miR-200a 的量化工具。此研究的創新之處為利用數位式聚合酶連鎖反應的技術，來進行多套式聚合酶連鎖反應，建立一個同時檢測 miR-21 和 miR-200a 的新方法，該方法有望成為一個靈敏且精確的卵巢癌診斷工具。

Ovarian cancer (OvCa) is one of the worldwide, fatal gynecological cancers due to its vague symptoms at early stages. Currently, there is a lack of efficient screening method for early diagnosis of OvCa. Extracellular vesicle (EV)-encapsulated microRNA (miRNA) has been emerged as novel, potential biomarkers for OvCa diagnosis. This study therefore developed an integrated microfluidic system for performing automated liquid biopsy-based EV-miRNA detection and quantification. The microfluidic chip has a capability of automating the entire experimental process, such as EVs extraction, EVs lysis, miRNA extraction and miRNA detection/quantification, on one chip within 5.5 hours (EVs extraction: 2.5 hours; EVs lysis: 3 min; miRNA extraction: 40 min; RT-qPCR: 2 hours). The results showed that the capture rate of total plasma EVs were determined to be ~52% which was comparable to the previously reported work (~54%) with operating time decreased by 37%, which attributes to the utilization of the anti-CD63/anti-EpCAM beads. In addition, this study developed a multiplex profiling of miR-21 and miR-200a, which could contribute to a higher sensitivity and specificity for OvCa diagnosis than that only miR-21 was detected previously. Experimental results showed that the calibration curves derived from the multiplex real-time PCR (quantitative PCR, qPCR) assay could exhibit a high linearity, hence provided as a highly specific, reliable quantification tool for simultaneous miR-21/miR-200a detection. Herein, we reported a novel method of simultaneous detection of miR-21 and miR-200a by implementing a multiplex qPCR assay. The uniqueness of this microfluidic system was attributed to its 1) integration of EVs extraction, EVs lysis and miRNA extraction process, 2) simultaneous multiplex miRNA detection, and 3) miniaturization and automation of the whole procedure.

Abstract 2
Acknowledgements 4
Table of contents 5
List of tables 8
List of figures 9
Abbreviations and nomenclature 11
Chapter 1 Introduction 13
1.1 Bio-MEMS based microfluidics 13
1.2 Early detection of ovarian cancer (OvCa) 14
1.3 Extracellular vesicles (EVs) and microRNA (miRNA) 15
1.4 Multiplex qPCR 16
1.5 Objectives and novelty 17
Chapter 2 Materials and methods 19
2.1 Multiplex qPCR assay for rapid diagnosis of ovarian cancer 19
2.2 Isolation of plasma EVs using anti-CD63 and anti-EpCAM beads 19
2.3 Extraction and multiplex detection of miRNA 20
2.4 Design of the integrated microfluidic chip 21
2.5 The experimental procedures of the multiplex qPCR assay 23
2.6 Entire experimental procedure on the microfluidic chip 25
2.7 Microfabrication process of the integrated microfluidic chip 29
Chapter 3 Results and discussion 31
3.1 Characterization of micro-components 31
3.2 Plasma EVs capture efficiency 32
3.3 Capture efficiencies for miR-21 and miR-200a 35
3.4 Calibration curves derived from multiplex qPCR 37
3.5 Specificity tests of multiplex qPCR 38
Table 3-2: Specificity tests of multiplex qPCR assay for miR-21. (N=3) 39
Table 3-3: Specificity tests of multiplex qPCR assay for miR-200a. (N=3) 39
3.8 Clinical sample tests 41
Chapter 4 Conclusions and future works 44
4.1 Conclusions 44
4.2 Future Works 46
4.2.1 Absolute quantification of miR-21 and miR-200a using multiplex dPCR module 46
4.2.2 False-positive/-negative rates of the dPCR module 46
4.2.2 Comparison between the dPCR module and conventional benchtop PCR assay 47
4.2.3 Integration of EVs/miRNA extraction module and multiplex dPCR module 48
References 49
Publication list 52

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