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  1. NTU Theses and Dissertations Repository
  2. 醫學院
  3. 生物化學暨分子生物學科研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/78369
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor李明學(Ming-Shyue Lee)
dc.contributor.authorYa-Tien Chiuen
dc.contributor.author邱雅甜zh_TW
dc.date.accessioned2021-07-11T14:53:26Z-
dc.date.available2025-07-20
dc.date.copyright2020-09-10
dc.date.issued2020
dc.date.submitted2020-07-20
dc.identifier.citation1 Siegel, R. L., Miller, K. D. Jemal, A. Cancer statistics, 2019. CA Cancer J Clin 69, 7-34, doi:10.3322/caac.21551 (2019).
2 Taitt, H. E. Global Trends and Prostate Cancer: A Review of Incidence, Detection, and Mortality as Influenced by Race, Ethnicity, and Geographic Location. American Journal of Mens Health 12, 1807-1823, doi:10.1177/1557988318798279 (2018).
3 Yang, D. D., Mahal, B. A., Muralidhar, V., Nezolosky, M. D., Vastola, M. E., Labe, S. A., Boldbaatar, N., King, M. T., Martin, N. E., Orio, P. F., 3rd, Beard, C. J., Hoffman, K. E., Trinh, Q. D., Spratt, D. E., Feng, F. Y. Nguyen, P. L. Risk of Upgrading and Upstaging Among 10 000 Patients with Gleason 3+4 Favorable Intermediate-risk Prostate Cancer. Eur Urol Focus 5, 69-76, doi:10.1016/j.euf.2017.05.011 (2019).
4 Gearman, D. J., Morlacco, A., Cheville, J. C., Rangel, L. J. Karnes, R. J. Comparison of Pathological and Oncologic Outcomes of Favorable Risk Gleason Score 3 + 4 and Low Risk Gleason Score 6 Prostate Cancer: Considerations for Active Surveillance. J Urol 199, 1188-1195, doi:10.1016/j.juro.2017.11.116 (2018).
5 Kamel, M. H., Khalil, M. I., Alobuia, W. M., Su, J. Davis, R. Incidence of metastasis and prostate-specific antigen levels at diagnosis in Gleason 3+4 versus 4+3 prostate cancer. Urol Ann 10, 203-208, doi:10.4103/UA.UA_124_17 (2018).
6 Thomsen, F. B., Roder, M. A., Hvarness, H., Iversen, P. Brasso, K. Active surveillance can reduce overtreatment in patients with low-risk prostate cancer. Dan Med J 60, A4575 (2013).
7 Tosoian, J. J., Mamawala, M., Epstein, J. I., Landis, P., Wolf, S., Trock, B. J. Carter, H. B. Intermediate and Longer-Term Outcomes From a Prospective Active-Surveillance Program for Favorable-Risk Prostate Cancer. J Clin Oncol 33, 3379-3385, doi:10.1200/JCO.2015.62.5764 (2015).
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9 Loeb, S., Bjurlin, M. A., Nicholson, J., Tammela, T. L., Penson, D. F., Carter, H. B., Carroll, P. Etzioni, R. Overdiagnosis and overtreatment of prostate cancer. Eur Urol 65, 1046-1055, doi:10.1016/j.eururo.2013.12.062 (2014).
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13 Huang, Y., Li, Z. Z., Huang, Y. L., Song, H. J. Wang, Y. J. Value of free/total prostate-specific antigen (f/t PSA) ratios for prostate cancer detection in patients with total serum prostate-specific antigen between 4 and 10 ng/mL: A meta-analysis. Medicine (Baltimore) 97, e0249, doi:10.1097/MD.0000000000010249 (2018).
14 Rubin, M. A., Zhou, M., Dhanasekaran, S. M., Varambally, S., Barrette, T. R., Sanda, M. G., Pienta, K. J., Ghosh, D. Chinnaiyan, A. M. alpha-Methylacyl coenzyme A racemase as a tissue biomarker for prostate cancer. JAMA 287, 1662-1670, doi:10.1001/jama.287.13.1662 (2002).
15 Alshalalfa, M., Verhaegh, G. W., Gibb, E. A., Santiago-Jimenez, M., Erho, N., Jordan, J., Yousefi, K., Lam, L. L. C., Kolisnik, T., Chelissery, J., Seiler, R., Ross, A. E., Karnes, R. J., Schaeffer, E. M., Lotan, T. T., Den, R. B., Freedland, S. J., Davicioni, E., Klein, E. A. Schalken, J. A. Low PCA3 expression is a marker of poor differentiation in localized prostate tumors: exploratory analysis from 12,076 patients. Oncotarget 8, 50804-50813, doi:10.18632/oncotarget.15133 (2017).
16 Nunes, J., Naymark, M., Sauer, L., Muhammad, A., Keun, H., Sturge, J., Stebbing, J., Waxman, J. Pchejetski, D. Circulating sphingosine-1-phosphate and erythrocyte sphingosine kinase-1 activity as novel biomarkers for early prostate cancer detection. Br J Cancer 106, 909-915, doi:10.1038/bjc.2012.14 (2012).
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19 Laxman, B., Morris, D. S., Yu, J., Siddiqui, J., Cao, J., Mehra, R., Lonigro, R. J., Tsodikov, A., Wei, J. T., Tomlins, S. A. Chinnaiyan, A. M. A first-generation multiplex biomarker analysis of urine for the early detection of prostate cancer. Cancer Res 68, 645-649, doi:10.1158/0008-5472.CAN-07-3224 (2008).
20 Brikun, I., Nusskern, D. Freije, D. An expanded biomarker panel for the detection of prostate cancer from urine DNA. Exp Hematol Oncol 8, 13, doi:10.1186/s40164-019-0137-x (2019).
21 Kachakova, D., Mitkova, A., Popov, E., Beltcheva, O., Vlahova, A., Dikov, T., Hristova, S., Mitev, V., Slavov, C. Kaneva, R. Evaluation of the clinical value of the newly identified urine biomarker HIST1H4K for diagnosis and prognosis of prostate cancer in Bulgarian patients. J BUON 18, 660-668 (2013).
22 Jarrard, W. E., Schultz, A., Etheridge, T., Damodaran, S., Allen, G. O., Jarrard, D. Yang, B. Screening of urine identifies PLA2G16 as a field defect methylation biomarker for prostate cancer detection. PLoS One 14, e0218950, doi:10.1371/journal.pone.0218950 (2019).
23 Woodson, K., O'Reilly, K. J., Hanson, J. C., Nelson, D., Walk, E. L. Tangrea, J. A. The usefulness of the detection of GSTP1 methylation in urine as a biomarker in the diagnosis of prostate cancer. J Urol 179, 508-511; discussion 511-502, doi:10.1016/j.juro.2007.09.073 (2008).
24 Fujita, K. Nonomura, N. Urinary biomarkers of prostate cancer. Int J Urol 25, 770-779, doi:10.1111/iju.13734 (2018).
25 Wu, F., Wang, P., Young, L. C., Lai, R. Li, L. Proteome-wide identification of novel binding partners to the oncogenic fusion gene protein, NPM-ALK, using tandem affinity purification and mass spectrometry. The American journal of pathology 174, 361-370, doi:10.2353/ajpath.2009.080521 (2009).
26 Hessels, D., Smit, F. P., Verhaegh, G. W., Witjes, J. A., Cornel, E. B. Schalken, J. A. Detection of TMPRSS2-ERG fusion transcripts and prostate cancer antigen 3 in urinary sediments may improve diagnosis of prostate cancer. Clin Cancer Res 13, 5103-5108, doi:10.1158/1078-0432.CCR-07-0700 (2007).
27 Pettersson, A., Graff, R. E., Bauer, S. R., Pitt, M. J., Lis, R. T., Stack, E. C., Martin, N. E., Kunz, L., Penney, K. L., Ligon, A. H., Suppan, C., Flavin, R., Sesso, H. D., Rider, J. R., Sweeney, C., Stampfer, M. J., Fiorentino, M., Kantoff, P. W., Sanda, M. G., Giovannucci, E. L., Ding, E. L., Loda, M. Mucci, L. A. The TMPRSS2:ERG rearrangement, ERG expression, and prostate cancer outcomes: a cohort study and meta-analysis. Cancer Epidemiol Biomarkers Prev 21, 1497-1509, doi:10.1158/1055-9965.EPI-12-0042 (2012).
28 Robert, G., Jannink, S., Smit, F., Aalders, T., Hessels, D., Cremers, R., Mulders, P. F. Schalken, J. A. Rational basis for the combination of PCA3 and TMPRSS2:ERG gene fusion for prostate cancer diagnosis. Prostate 73, 113-120, doi:10.1002/pros.22546 (2013).
29 Stephan, C., Jung, K., Semjonow, A., Schulze-Forster, K., Cammann, H., Hu, X., Meyer, H. A., Bogemann, M., Miller, K. Friedersdorff, F. Comparative assessment of urinary prostate cancer antigen 3 and TMPRSS2:ERG gene fusion with the serum [-2]proprostate-specific antigen-based prostate health index for detection of prostate cancer. Clin Chem 59, 280-288, doi:10.1373/clinchem.2012.195560 (2013).
30 Jo, E., Jang, H. J., Yang, K. E., Jang, M. S., Huh, Y. H., Yoo, H. S., Park, J. S., Jang, I. S. Park, S. J. Cordyceps militaris induces apoptosis in ovarian cancer cells through TNF-alpha/TNFR1-mediated inhibition of NF-kappaB phosphorylation. BMC Complement Med Ther 20, 1, doi:10.1186/s12906-019-2780-5 (2020).
31 Yang, S. Z., Xu, F., Zhou, T., Zhao, X., McDonald, J. M. Chen, Y. The long non-coding RNA HOTAIR enhances pancreatic cancer resistance to TNF-related apoptosis-inducing ligand. J Biol Chem 292, 10390-10397, doi:10.1074/jbc.M117.786830 (2017).
32 Song, Y., Gao, J., Guan, L., Chen, X., Gao, J. Wang, K. Inhibition of ANO1/TMEM16A induces apoptosis in human prostate carcinoma cells by activating TNF-alpha signaling. Cell Death Dis 9, 703, doi:10.1038/s41419-018-0735-2 (2018).
33 Greer, Y. E., Gilbert, S. F., Gril, B., Narwal, R., Peacock Brooks, D. L., Tice, D. A., Steeg, P. S. Lipkowitz, S. MEDI3039, a novel highly potent tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) receptor 2 agonist, causes regression of orthotopic tumors and inhibits outgrowth of metastatic triple-negative breast cancer. Breast Cancer Res 21, 27, doi:10.1186/s13058-019-1116-1 (2019).
34 Qin, W., Xiong, Y., Chen, J., Huang, Y. Liu, T. DC-CIK cells derived from ovarian cancer patient menstrual blood activate the TNFR1-ASK1-AIP1 pathway to kill autologous ovarian cancer stem cells. J Cell Mol Med 22, 3364-3376, doi:10.1111/jcmm.13611 (2018).
35 Holdbrooks, A. T., Britain, C. M. Bellis, S. L. ST6Gal-I sialyltransferase promotes tumor necrosis factor (TNF)-mediated cancer cell survival via sialylation of the TNF receptor 1 (TNFR1) death receptor. J Biol Chem 293, 1610-1622, doi:10.1074/jbc.M117.801480 (2018).
36 Fukuoka, S. I., Freedman, S. D. Scheele, G. A. A SINGLE GENE ENCODES MEMBRANE-BOUND AND FREE FORMS OF GP-2, THE MAJOR GLYCOPROTEIN IN PANCREATIC SECRETORY (ZYMOGEN) GRANULE MEMBRANES. Proc. Natl. Acad. Sci. U. S. A. 88, 2898-2902, doi:10.1073/pnas.88.7.2898 (1991).
37 Hao, Y., Wang, J., Feng, N. G. Lowe, A. W. Determination of plasma glycoprotein 2 levels in patients with pancreatic disease. Arch. Pathol. Lab. Med. 128, 668-674 (2004).
38 Muraoka, S., Kume, H., Watanabe, S., Adachi, J., Kuwano, M., Sato, M., Kawasaki, N., Kodera, Y., Ishitobi, M., Inaji, H., Miyamoto, Y., Kato, K. Tomonaga, T. Strategy for SRM-based Verification of Biomarker Candidates Discovered by iTRAQ Method in Limited Breast Cancer Tissue Samples. J. Proteome Res. 11, 4201-4210, doi:10.1021/pr300322q (2012).
39 Akiba, S., Hayashi, Y., Hakamada, Y., Endo, K., Ara, K., Kawai, S. Saitoh, E. Extracellular production of human cystatin S and cystatin SA by Bacillus subtilis. Protein Expr. Purif. 49, 203-210, doi:10.1016/j.pep.2006.04.005 (2006).
40 Keppler, D. Towards novel anti-cancer strategies based on cystatin function. Cancer Lett. 235, 159-176, doi:10.1016/j.canlet.2005.04.001 (2006).
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42 Zhang, Y. Q., Zhang, J. J., Song, H. J. Li, D. W. Overexpression of CST4 promotes gastric cancer aggressiveness by activating the ELFN2 signaling pathway. Am. J. Cancer Res. 7, 2290-2304 (2017).
43 Watanabe, T., Yonekura, H., Terazono, K., Yamamoto, H. Okamoto, H. COMPLETE NUCLEOTIDE-SEQUENCE OF HUMAN REG GENE AND ITS EXPRESSION IN NORMAL AND TUMORAL TISSUES - THE REG PROTEIN, PANCREATIC STONE PROTEIN, AND PANCREATIC THREAD PROTEIN ARE ONE AND THE SAME PRODUCT OF THE GENE. J. Biol. Chem. 265, 7432-7439 (1990).
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/78369-
dc.description.abstract攝護腺癌 (prostate cancer, PCa) 在已開發國家中是一個常好發於男性的惡性腫瘤,也包括台灣。然而,攝護腺癌不是一個致死率高的癌症,並非所有的攝護腺癌病人最終是死於癌症本身。因此,如何區分出致死性與非致死性的攝護腺癌,在臨床上是一項重要的課題。對於非致死性攝護腺癌病人,採取主動監測 (active surveillance) 的方式能夠降低過度治療 (over-treatment) 的問題,也可以避免積極性治療造成的副作用並使病人有較好的生活品質。在本篇研究中,我們考量到前列腺液能夠分泌到尿液中的特性,因此提出在致死性與非致死性攝護腺癌病人的尿液之中,存有能夠作為鑑別這兩組病人的生物標記 (biomarker)。為了找出這些生物標記蛋白,我們利用液相色譜與串聯質譜分析 (Liquid chromatography tandem mass spectrometry, LC-MS/MS) 對病人尿液中的蛋白進行蛋白質身分鑑
定,並利用正交偏最小平方判別分析法 (Orthogonal partial least squares discriminant analysis, OPLS-DA) 對資料進行降維分析,且鑑別出兩組病人尿液之中有顯著差異的蛋白圖譜。分析之後,我們找出五個在致死性攝護腺癌病人尿液中有顯著下降的蛋白生物標記 (significant PCa biomarkers, SPBs)。在診斷及區分致死性與非致死性攝護腺癌病人方面,SPBs在接收操作特徵圖 (receiver operating characteristic curve, ROC curve) 中的曲線下面積 (area under curve, AUC) 可以達到 0.933,而敏感度與特異性則分別可以達到88%與89%,優於現行血液中攝護腺癌生物標記-攝護腺特異性抗原 (prostate specific antigen, PSA) 之表現。此外,SPBs也能夠增加PSA診斷的準確度,當合併SPBs與PSA時,AUC能夠提升至0.967。我們另外也探討了SPBs作為預後指標的可能性,結果發現在接受特定治療如雄性素剝奪療法 (androgen deprivation therapy, ADT)、男性荷爾蒙抑制劑療法 (Abiraterone及Enzalutamide) 以及全身性化療的病人之中,SPBs也具有作為病人預後指標的潛力。總結來說,我們的結果支持SPBs能夠在臨床上作為鑑別致死性與非致死性攝護腺癌病人的尿液中生物標記。另外,SPBs也能夠做為治療中癌症病人的預後指標,在療程中監控病人對藥物治療之反應,並能夠及時調整及改善對於病人的治療方針。
zh_TW
dc.description.abstractProstate cancer (PCa) is a common male malignancy in developed countries including
Taiwan. However, not all PCa leads to cancer death. Stratification of PCa patients who are lethal or non-lethal will be an important issue to prevent over-treatment and keep life of quality of patients. In this study, we took advantage of the fact that the secretory fluid from prostate has a direct access to urine, and proposed that the protein profiles of lethal PCa patients’ urine may be distinct from those in the non-lethal PCa patients. We then used LC-MS/MS analysis and a supervised approach [Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA)] for the urine sample analyses, and isolated five significant PCa biomarkers (SPBs) with a dramatic decrease in the lethal PCa patient urine samples. In ROC analysis, the prediction ability of the SPBs in lethal PCa and nonlethal PCa patients revealed the AUC value of 0.933, with 0.88 for sensitivity and 0.89 for specificity. Moreover, SPBs could enhance the accuracy of serum PSA in diagnosis, and the AUC value when combined with serum PSA level was up to 0.967. Extensively, SPBs also had the potentials to be the prediction markers for the PCa patients under clinical treatments including androgen deprivation therapy (ADT), abiraterone, enzalutamide and systemic chemotherapy. In conclusion, our results suggest that SPBs exhibit a potential to be clinical urinary biomarkers to distinguish lethal PCa from nonlethal PCa. Moreover, SPBs might be potentially used as a prognostic marker to monitor the treatment responses during the therapeutic courses and give PCa patients more appropriate therapies.
en
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en
dc.description.tableofcontents致謝 ii
中文摘要 iii
Abstract v
Chapter 1. Introduction 1
1.1. Prostate cancer 2
1.2. Classification of human prostate cancer and characteristics of significant, insignificant, intermediate, and metastatic prostate cancer (sPC, isPC, imPC, and mPC) 3
1.3. Overtreatment of prostate cancer 5
1.4. Current biomarker-PSA and the unmet need 6
1.5. New biomarkers for prostate cancer 7
1.6. Research motivation 8
Chapter 2. Materials and Methods 9
2.1. Materials 10
2.1.1. Antibodies 10
2.1.2. ELISA kits 10
2.1.3. Reagents 10
2.1.4. Organic solvents 11
2.2. Methods 11
2.2.1. Urine samples collection 11
2.2.2. Urine sample preparation and LC-MS/MS analysis 12
2.2.3. ELISA 13
2.2.4. Western blot 14
2.2.5. Immunohistochemistry 15
2.2.6. Discriminant analysis of isPC and sPC 16
2.2.7. Statistical analysis 17
Chapter 3. Results 19
3.1. Procedure for identification of urine protein biomarkers to stratify PCa patients and the clinical information of the PCa patients in training cohort. 20
3.2. Principle component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA) and logistic regression used to identify useful protein biomarkers in PCa patients’ urine samples after LC-MS/MS analysis. 21
3.3. K fold cross validation and external validation of SPBs. 23
3.4. Fold changes of SPBs in sPC/mPC patients compared to benign/isPC patients. 24
3.5. Ingenuity Pathway Analysis (IPA) of SPBs 25
3.6. SPBs prediction capability when combined with patients’ serum PSA levels. 25
3.7. SPBs level in urinary samples were differentially changed in sPC patients. 27
3.8. Analysis of the relationship between the gene level of SPBs and Gleason scores in the PCa clinical database. 28
3.9. The relationship between the level of SPBs and the survival rate in the PCa clinical database. 28
3.10. SPBs predicted the clinical outcome after ADT combined with radiation therapy. 29
3.11. SPBs detected by ELISA predicted the clinical therapeutic outcome in PCa patients with different therapies. 30
3.12. SPBs expression levels in prostate cancer tissues with different Gleason scores. 32
Chapter 4. Discussion 33
Chapter 5. Figure 41
Chapter 6. Reference 66
dc.language.isoen
dc.subject預後zh_TW
dc.subject攝護腺癌zh_TW
dc.subject致死性攝護腺癌zh_TW
dc.subject過度治療zh_TW
dc.subject尿液生物標記zh_TW
dc.subject診斷zh_TW
dc.subjectlethal prostate canceren
dc.subjectprostate canceren
dc.subjectprognosisen
dc.subjectdiagnosisen
dc.subjecturinary biomarkersen
dc.subjectover-treatmenten
dc.title惡性攝護腺癌病人尿液中生物標記之探討與其作為預後指標之應用zh_TW
dc.titleIdentification of urinary biomarkers and prognostic indicators of significant prostate cancer patientsen
dc.typeThesis
dc.date.schoolyear108-2
dc.description.degree碩士
dc.contributor.oralexamcommittee蕭培文(Pei-Wen Hsiao),陳忠信(Chung-Hsin Chen),黃祥博(Hsiang-Po Huang),張凱雄(Kai-Hsiung Chang)
dc.subject.keyword攝護腺癌,致死性攝護腺癌,過度治療,尿液生物標記,診斷,預後,zh_TW
dc.subject.keywordprostate cancer,lethal prostate cancer,over-treatment,urinary biomarkers,diagnosis,prognosis,en
dc.relation.page72
dc.identifier.doi10.6342/NTU202001667
dc.rights.note有償授權
dc.date.accepted2020-07-21
dc.contributor.author-college醫學院zh_TW
dc.contributor.author-dept生物化學暨分子生物學研究所zh_TW
dc.date.embargo-lift2025-07-20-
顯示於系所單位:生物化學暨分子生物學科研究所

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