臺灣博碩士論文加值系統

卵巢癌，又稱為“婦女的隱形殺手”。台灣每年約會有1300個新案例發生，而其死亡率在女性癌症中排名第七位，更是在婦科癌症中排名第一。主要原因為卵巢癌難以在早期被篩檢出。早期卵巢癌的五年存率有92%，而到了晚期，五年存活率掉到僅僅17%，因此如何有效且準確的在早期就發現卵巢癌是非常重要的。近期BRAC1基因變異已經被證實與卵巢癌的發生有很大的關連，有此基因變異的群眾往往有更高的機率會罹患卵巢癌。液態檢體是一門新興的技術，提供了需多關於腫瘤資訊的生物標記物如: 游離DNA，許多篇研究也在游離DNA中發現BRAC1基因變異，可提供卵巢癌的檢測及評估新的工具。因此本研究欲利用微流體系統來自動化萃取病人血漿檢體中的游離DNA並檢測BRAC1的基因變異來提供臨床醫生風險評估。此系統整合了兩個模組: 第一模組為”游離DNA萃取模組”利用渦流型微混和器均勻混和游離DNA及類矽磁珠，能在45分鐘內從200微升的血漿檢體萃取游離DNA並達到76%抓取率；第二模組為”游離DNA定量模組”，運用連動式微幫浦平均分配4.5微升的純化檢體進入反應區並執行90分鐘的晶片上即時單核苷酸多態性聚合酶連鎖反應，目前檢測極限達到50拷貝數。藉由自動化游離DNA萃取及定量過程，此發展系統在”晶片實驗室”的應用有很好的潛力。

Ovarian cancer is known as "a silent killer of women". In Taiwan, there are 1,300 new cases each year, and its mortality rate ranks the seventh among female cancers and the first among gynecological cancers. It is due to the fact that ovarian cancer is difficult to be diagnosed at early stages. The five-year survival rate of early-stage ovarian cancer is 92%, but at the late stages, drops to only 17%. Thus, early diagnosis of ovarian cancer is critical. Recently, BRCA1 gene mutations have been confirmed to be highly related to the occurrence of ovarian cancer. It is evident that patients with this gene mutation usually have a higher chance of developing ovarian cancer in their lifetime. Liquid biopsy such as cell-free DNA (cfDNA) is an emerging technology that brings more information about tumors from the blood. Many studies have found BRAC1 gene mutations in cfDNA could serve a potential tool for diagnosis and risk assessment of ovarian cancer. Therefore, an integrated microfluidic system was developed in this work to automatically extract cfDNA from patient plasma samples and detect BRAC1 germline and somatic mutations to provide clinicians a risk assessment in an automatic format within 120 min. Two modules were integrated in this system; the first module was called “cfDNA extraction module” equipped with a vortex-type micromixer that can mix cfDNA and silica-like magnetic beads to achieve an extraction rate of 76% from 200 µL of plasma sample in 45 min. The second module was a “cfDNA quantification module” which activated a consecutive micropump to distribute 4.5 µL of purified cfDNA sample evenly into reaction zones to perform on-chip real-time single nucleotide polymorphism polymerase chain reaction (SNP-qPCR) within 90 min. The limit of detection was found to be as low as 50 copies. By automating the cfDNA extraction and cfDNA quantification process, the developed system presents a great potential for lab-on-a-chip (LOC) applications.

Abstract 2
摘要 4
致謝 5
Table of Contents 7
List of figures 10
List of tables 19
Nomenclature and abbreviations 21
Chapter 1 Introduction 24
1.1 Ovarian cancer 24
1.2 BRCA1 gene mutation 26
1.3 Liquid biopsy and cell-free DNA 28
1.3.1 Cell-free DNA and ovarian cancer 28
1.3.2 Microfluidic applications on cell-free DNA 29
1.4 Single nucleotide polymorphism polymerase chain reaction (SNP-PCR) 30
1.5 Motivation and novelty 32
Chapter 2 Materials and methods 35
2.1 Preparation of samples and reagents 35
2.1.1 BRCA1 germline/somatic mutation specific primers 35
2.1.2 DNA samples and PCR reagents preparation 41
2.1.3 Clinical samples preparation 42
2.1.5 cfDNA quantification by arthrobacter luteus (ALU) primers 48
2.2 Chip design and microfabrication 50
2.3 Working principle and characterization of microfluidic chip 56
2.3.1 Pneumatic microvalves and micropumps 56
2.3.2 Vortex-typed micromixer 58
2.4 Experimental setup and procedure 61
Chapter 3 Results and discussion 65
3.1 Characterization of the integrated microfluidic chip 65
3.1.1 Pumping volume and uniformity of micropump 65
3.1.2 Mixing index of vortex-typed micromixer 70
3.2 Optimization of cfDNA extraction 72
3.2.1 Calibration curve and recovery rate calculation 72
3.2.2 Capture rate of cfDNA 72
3.3 SNP-PCR for detecting BRAC1 mutation 75
3.3.1 Optimization of on-bench SNP-PCR condition for germline mutation 75
3.3.2 Optimization of on-bench SNP-PCR condition for somatic mutation 77
3.3.3 Spiked experiments of BRAC1 mutation detection 77
3.4 SNP-qPCR for detecting BRAC1 mutation 80
3.4.1 Optimization of on-bench SNP-qPCR condition for germline mutation 80
3.4.2 On-chip SNP-qPCR for germline mutation 80
3.4.3 Optimization of on-bench SNP-qPCR operating condition for somatic mutation 85
3.4.4 On-chip SNP-qPCR for somatic mutation 85
3.5 Sensitivity tests of BRCA1 mutation detection on the microfluidic platform 90
3.5.1 Limit of detection of SNP-PCR 90
3.5.2 Limit of detection of SNP-qPCR 90
3.6 Specificity tests of BRCA1 mutation detection on the microfluidic platform 95
3.7 Cell-line tests by SNP-PCR 97
3.8 Clinical tests by SNP-PCR 100
3.8.1 Clinical tests by SNP-PCR 100
3.8.1 Spiked experiments of clinical samples 105
Chapter 4 Conclusions and future perspectives 109
4.1 Conclusions 109
4.2 Future perspectives 111
4.2.1 Clinical tests 111
4.2.2 LOD of the microfluidic system 111
4.2.3 Increase detection numbers on the microfluidic chip 111
4.2.4 Specific primers for real-time PCR 112
4.2.5 Ovarian cancer prognosis 112
References 113
Supplementary information 122

[1] R. L. Siegel, K. D. Miller, A. Jemal, “Cancer statistics, 2019”, A Cancer Journal for Clinicians, vol. 69, pp. 7-34, 2019.
[2] K. K. Gupta, V. K. Gupta, R. W. Naumann, “Ovarian cancer: screening and future directions”, International Journal of Gynecological Cancer 2019, vol. 29, pp. 195-200, 2019.
[3] P. M. Das, R. C. Bast Jr., “Early detection of ovarian cancer”, Biomarkers in Medicine, vol. 2, pp. 291-303, 2008.
[4] J. R. van Nagell Jr., J. T. Hoff, “Transvaginal ultrasonography in ovarian cancer screening: current perspectives”, International Journal of Women’s Health 2014, vol. 6, pp. 25-33, 2014.
[5] R. L. Milne, A. Osorio, T. Ramón Y Cajal, A. Vega, G. Llort, M. Hoya, O. Diez, M. Alonso, C. Lázaro, I. Blanco, A. Sánchez-de-Abajo, T. Caldés, A. Blanco, B. Graña, M. Durán, E. Velasco, I. Chirivella, E. Cardeñosa, M. Tejada, J. Benítez, “The average cumulative risks of breast and ovarian cancer for carriers of mutations in BRCA1 and BRCA2 attending genetic counseling units in Spain”, Clinical Cancer Research, vol. 14, pp. 2861-2869, 2008.
[6] R. T. Neff, L. Senter, R. Salani, “BRCA mutation in ovarian cancer: testing, implications and treatment considerations”, Therapeutic Advances in Medical Oncology, vol. 9, pp. 519-531, 2017.
[7] K. B. Kuchenbaecker, J. L. Hopper, D. R. Barnes, K. A. Phillips, T. M. Mooij, M. M. B. Terry, M. A. Rookus, D. F. Easton, A. C. Antoniou, “Risks of breast, ovarian, and contralateral breast cancer for BRCA1 and BRCA2 mutation carriers”, Journal of the American Medical Association, vol. 317, pp. 2402-2416, 2017.
[8] M. Ratajska, M. Koczkowska, M. Żuk, A. Gorczyński, A. Kuźniacka, M. Stukan, W. Biernat, J. Limon, B. Wasąg, “Detection of BRAC1/BRCA2 mutations in circulating tumor DNA from patients with ovarian cancer”, Oncotarget, vol. 8, pp. 101325-101332, 2017.
[9] Douvdevani, R. B. Molho, K. Asraf, R. Doolman, Y. Laitman, E. Friedman, “Circulating cell-free DNA (cfDNA) levels in BRCA1 and BRCA2 mutation carriers: a preliminary study”, Cancer Biomarkers, vol. 28, pp. 269-273, 2020.
[10] M. Elazezy, S. A. Joosse, “Techniques of using circulating tumor DNA as a liquid biopsy component in cancer management”, Computational and Structural Biotechnology Journal, vol. 16, pp. 370-378, 2018.
[11] S. A. Joosse, K. Pantel, “Tumor-educated platelets as liquid biopsy in cancer patients”, Cancer Cell, vol. 28, pp. 552-554, 2015.
[12] G. Barbany, C. Arthur, A. Liedén, M. Nordenskjöld, R. Rosenquist, B. Tesi, K. Wallander, E. Tham, “Cell-free tumor DNA testing for early detection of cancer – a potential future tool”, Journal of Internal Medicine, vol. 286, pp. 118-136, 2019.
[13] A. Kamat, A. K. Sood, D. Dang, D. M. Gershenson, J. L. Simpson, F. Z. Bischoff, “Quantification of total plasma cell-free DNA in ovarian cancer using real-time PCR”, Annals of the New York Academy of Sciences, vol. 1075, pp. 230-234, 2006.
[14] R. Mari, E. Mamessier, E. Lambaudie, M. Provansal, D. Birnbaum, F. Bertucci, R. Sabatier, “Liquid biopsies for ovarian carcinoma: how blood tests may improve the clinical management of a deadly disease”, Cancers, vol. 11, pp. 774, 2019.
[15] W. Gai, K. Sun, “Epigenetic biomarkers in cell-free DNA and applications in liquid biopsy”, Genes, vol. 10, pp. 32, 2019.
[16] Z. Xu, Y. Qiao, J. Tu, “Microfluidic technologies for cfDNA isolation and analysis”, Micromachines, vol. 10, pp. 672, 2019.
[17] K. Perez-Toralla, I. Pereiro, S. Garrigou, F. D. Federico, C. Proudhon, F. C. Bidard, J. L. Viovy, V. Taly, S. Descroix, “Microfluidic extraction and digital quantification of circulating cell-free DNA from serum”, Sensors and Actuators B: Chemical, vol. 286, pp. 533-539, 2019.
[18] C. Campos, S. Gamage, J. M. Jackson, M. Witek, D. S. Park, M. C. Murphy, A. K. Godwin, S. A. Soper, “Microfluidic-based solid phase extraction of cell free DNA”, Lab on a Chip, vol. 18, pp. 3459-3470, 2018.
[19] C. E. Jin, B. Koo, T. Y. Lee, K. Han, S. B. Lim, I. J. Park, Y. Shin, “Simple and low-cost sampling of cell-free nucleic acids from blood plasma for rapid and sensitive detection of circulating tumor DNA”, Advanced Science, vol. 5, pp. 1800614, 2018.
[20] L. Ugozzoli, R. B. Wallace, “Allele-specific polymerase chain reaction”, Methods, vol. 2, pp. 42-48, 1991.
[21] K. B. Mathieu, D. G. Bedi, S. L. Thrower, A. Qayyum, R. C. B. Jr., “Screening for ovarian cancer: imaging challenges and opportunities for improvement”, Ultrasound in Obstetrics and Gynecology, vol. 51, pp. 293-303, 2018.
[22] Ş. Ari, M. Arikan, “Next-generation sequencing: advantages, disadvantages, and future”, Plant Omics: Trends and Applications, vol. 1, pp. 109-135, 2016.
[23] C. Y. Chao, C. H. Wang, Y. J. Che, C. Y. Kao, J. J. Wu, G. B. Lee, “An integrated microfluidic system for diagnosis of the resistance of Helicobacter pylori to quinolone-based antibiotics”, Biosensors and Bioelectronics, vol. 78, pp. 281-289, 2016.
[24] W. H. Kuo, P. H. Lin, A. C. Huang, Y. H. Chien, T. P. Liu, Y. S. Lu, L. Y. Bai, A. M. Sargeant, C. H. Lin, A. L. Cheng, F. J. Hsieh, W. L. Hwu, K. J. Chang, “Multimodel assessment of BRCA1 mutations in Taiwanese (ethnic Chinese) women with early-onset, bilateral of familial breast cancer”, Journal of Human Genetics, vol. 57, pp. 130-138, 2012.
[25] N. Umetani, J. Kim, S. Hiramatsu, H. A. Reber, O. J. Hines, A. J. Bilchik, D. S. B. Hoon, “Increased integrity of free circulating DNA in sera of patients with colorectal or periampullary cancer: direct quantitative PCR for ALU repeats”, Clinical Chemistry, vol. 52, pp. 1062-1069, 2006.
[26] S. Y. Yang, J. L. Lin, G. B. Lee, “A vortex-type micromixer utilizing pneumatically driven membranes”, Journal of Micromechanics and Microengineering, vol. 19, pp. 035020, 2009.
[27] C. H. Weng, K. Y. Lien, S. Y. Yang, G. B. Lee, “A suction-type, pneumatic microfluidic device for liquid transport and mixing”, Microfluid Nanofluid, vol. 10, pp. 301-310, 2011.
[28] K. M. Shen, N. M. Sabbavarapu, C. Y. Fu, J. T. Jan, J. R. Wang, S. C. Hung, G. B. Lee, “An integrated microfluidic system for rapid detection and multiple subtyping of influenza A viruses by using glycan-coated magnetic beads and RT-PCR”, Lab on a Chip, vol. 19, pp. 1277-1286, 2019.
[29] G. Schwarz, S. Bäumler, A. Block, F. Felsenstein, G. Wenzel, “Determination of detection and quantification limits for SNP allele frequency estimation in DNA pools using real time PCR”, Nucleic Acids Research, vol. 32, pp. e24, 2004.
[30] A. A. Kamat, M. Baldwin, D. Urbauer, D. Dang, L. Y. Han, A. Godwin, B. Y. Karlan, J. L. Simpson, D. M. Gershenson, R. L. Coleman, F. Z. Bischoff, A. K. Sood, “Plasma cell-free DNA in ovarian cancer: an independent prognostic biomarker”, Cancer, vol. 116, pp. 1918-1925, 2010.
[31] R. R. Zachariah, S. Schmid, N. Buerki, R. Radpour, W. Holzgreve, X. Y. Zhong, “Levels of circulating cell-free nuclear and mitochondrial DNA in benign and malignant ovarian tumors”, Obstetrics and Gynecology, vol. 112, pp. 4, 2008.
[32] C. Kohler, R. Radpour, Z. Barekati, R. Asadollahi, J. Bitzer, E. Wight, N. Bürki, C. Diesch, W. Holzgreve, X. Y. Zhong, “Levels of plasma circulating cell free nuclear and mitochondrial DNA as potential biomarkers for breast tumors”, Molecular Cancer, vol. 8, pp. 105, 2009.
[33] M. Okkonen, P. Lakkisto, A. M. Korhonen, I. Parviai-nen, M. Reinikainen, T. Varpula, V. Pettilä, “Plasma cell-free DNA in patients needing mechanical ventilation”, Critical Care, vol. 15, pp. 196, 2011.
[34] Q. Zhou, W. Li, B. Leng, W. Zheng, Z. He, M. Zuo, A. Chen, “Circulating cell free DNA as the diagnostic marker for ovarian cancer: a systematic review and meta-analysis”, PLoS ONE, vol. 11, pp. 6, 2016.
[35] X. Y. Zhong, I. Mu¨ hlenen, Y. Li, A. Kang, A. K. Gupta, A. Tyndall, W. Holzgreve, S. Hahn, P. Hasler, “Increased concentrations of antibody-bound circulatory cell-free DNA in rheumatoid arthritis”, Molecular Diagnostics and Genetics, vol. 53, pp. 1609-1614, 2007.
[36] Streubel, A. Stenzinger, S. Stephan-Falkenau, J. Kollmeier, D. Misch, T. G. Blum, T. Bauer, O. Landt, A. A. Ende, P. Schirmacher, T. Mairinger, V. Endris, “Comparison of different semi-automated cfDNA extraction methods in combination with UMI-based targeted sequencing”, Oncotarget, vol. 10, pp. 5690-5702, 2019.
[37] S. A. Bustin, V. Benes, J. A. Garson, J. Hellemans, J. Huggett, M. Kubista, R. Mueller, T. Nolan, M. W. Pfaffl, G. L. Shipley, J. Vandesompele, C. T. Wittwer, “The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments”, Clinical Chemistry, vol. 55, pp. 611-622, 2009.
[38] L. Dong, S. Wang, B. Fu, J. Wang, “Evaluation of droplet digital PCR and next generation sequencing for characterizing DNA reference material for KRAS mutation detection”, Scientific Reports, vol. 8, pp. 9650, 2018.
[39] Thierry, F. Mouliere, S. EL Messaoudi, C. Mollevi, E. Lopez-Crapez, F. Rolet, B. Gillet, C. Gongora, P. Déchelotte, B. Robert, M. Del Rio, P. J. Lamy, F. Bibeau, M. Nouaille, V. Loriot, A. S. Jarrousse, F. Molina, M. Mathonnet, D. Pezet, M. Ychou, “Clinical validation of the detection of KRAS and BRAF mutations from circulating tumor DNA”, Nature Medicine, vol. 20, pp. 430-435, 2014.
[40] H. Wang, J. Jiang, B. Mostert, A. Sieuwerts, J. Martens, S. Sleijfer, J. Foekens, Y. Wang, “Allele-specific, non-extendable primer blocker PCR (AS-NEPB-PCR) for DNA mutation detection in cancer”, The Journal of Molecular Diagnostics, vol. 15, pp. 62-69, 2013.
[41] K. L. Bolton , G. C. Trench, C. Goh, S. Sadetzki, S. J. Ramus, B. Y. Karlan, D. Lambrechts, E. Despierre, D. Barrowdale, L. McGuffog, S. Healey, D. F. Easton, O. Sinilnikova, J. Benitez, M. J. García, S. Neuhausen, M. H. Gail, P. Hartge, EMBRACE study team, S. Peock, D. Frost, D. G. Evans, R. Eeles, A. K. Godwin, M. B. Daly, Ava Kwong, Ed. SK. Ma, C. Lázaro, I. Blanco, M. Montagna, E. D’Andrea, O. Nicoletto, kConFab Investigators, S. E. Johnatty, S. Krüger Kjær, A. Jensen, E. Høgdall, E. L. Goode, B. L. Fridley, J. T. Loud, M. H. Greene, P. L. Mai, A. Chetrit, F. Lubin, G. H. Yechezkel, G. Glendon, I. L. Andrulis, A. E. Toland, L. Senter, M. E. Gore, C. Gourley, C. O Michie, H. Song, J. Tyrer, A. S. Whittemore, V. McGuire, W. Sieh, U. Kristoffersson, H. Olsson, Å. Borg, D. A. Levine, Cancer Genome Atlas Research Network, L. Steele, M. S. Beattie, S. Chan, R. Nussbaum, K. B. Moysich, J. Gross, I. Cass, C. Walsh, A. J. Li, R. Leuchter, O. Gordon, M. G. Closas, S. A. Gayther, S. J. Chanock, A. C. Antoniou, P. D.P. Pharoah, “Association between BRCA1 and BRCA2 mutations and survival in women with invasive epithelial ovarian cancer”, JAMA, vol. 307, pp. 382 – 390, 2012.
[42] J. Boyd, Y. Sonoda, M. G. Federici, F. Bogomolniy, E. Rhei, D. L. Maresco, P. E. Saigo, L. A. Almadrones, R. R. Barakat, C. L. Brown, D. S. Chi, J. P. Curtin, E. A. Poynor, W. J. Hoskins, “Clinicopathologic features of BRCA-linked and sporadic ovarian cancer”, JAMA, vol. 283, pp. 17, 2000.