請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/7545
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 李建南 | zh_TW |
dc.contributor.advisor | Chien-Nan Lee | en |
dc.contributor.author | 魯筱筠 | zh_TW |
dc.contributor.author | Hsiao-Yun Lu | en |
dc.date.accessioned | 2021-05-19T17:46:05Z | - |
dc.date.available | 2024-02-28 | - |
dc.date.copyright | 2018-10-09 | - |
dc.date.issued | 2018 | - |
dc.date.submitted | 2002-01-01 | - |
dc.identifier.citation | 1.Reid, B.M., et al., Epidemiology of ovarian cancer: a review. Cancer Biol Med, 2017.14(1):p9–32.
2.Pfleiderer, A., Diagnosis and staging of ovarian cancer. J Cancer Res Clin Oncol, 1984.107(2):p.81-8. 3.Gonzalez, D. P., et al., Tim trends in ovarian cancer mortality in Europe(1955-1993): effect of age, birth cohort and period of death. Eur J Cancer, 2000.36(14):p.1816-24. 4.Chiang, Y.C., et al., Trends in incidence and survival outcome of epithelial ovarian cancer:30-year national population-based registry in Taiwan. J Gynecol Oncol, 2013.24(4):p.342-51. 5.Siegel, R., et al., Cancer statistics, 2014. CA Cancer J Clin, 2014.64(1):p.9-29. 6.Rustin, G.J., Tumor markers for ovarian cancer. Eur J Cancer, 1992.28(1):p.2-3. 7.David, G.M., et al., 2014 FIGO staging for ovarian, fallopian tube and peritoneal cancer. Gynecologic Oncology, 2014.133(3):p.401-4. 8.Selvaggi, S.M., Tumors of the ovary, maldeveloped gonads, fallopian tube, and broad ligament. Arch Pathol Lab Med, 2000.124(3):p.477. 9.Doubeni, C.A., et al., Diagnosis and Management of Ovarian Cancer. Am Fam Physician, 2016.93(11):p.937-44. 10.Cliby, W., et al., Diaphragm resection for ovarian cancer: technique and short-term complications. Gynecol Oncol, 2004.94(3):p.655-60. 11.Dowdy, S.C., et al., Assesment of outcomes and morbidity following diaphragmatic peritonectomy for women with ovarian carcinoma. Gynecol Oncol, 2008.109(2):p.303-7. 12.Eisenhauer, E.L., et al., The addition of extensive upper abdominal surgery to achieve optimal cytoreduction improves survival in patients eith stages IIIC-IV epithelial ovarian cancer. Gynecol Oncol, 2006.103(3):p1083-90. 13.Hoffman, M.S., et al., Site of bowel resected to achieve optimal ovarian cancer cytoreduction: implications regarding surgical management. Am J Obstet Gynecol, 2005.193(2):p.582-8. 14.Tebes, S.J., et al., Colorectal resection in patients with ovarian and primary peritoneal carcinoma. Am J Obstet Gynecol, 2006.195(2): p.585-90. 15.Marchetti, C., et al., First-line treatment of advanced ovarian cancer: current research and perspectives. Expert Rev Anticancer Ther, 2010.10(1):p47-60 16.Davis, A., et al., "Platinum resistant" ovarian cancer: what is it, who to treat and how to measure benefit? Gynecol Oncol, 2014.133(3): p.624-31. 17.Coleman, R.L., et al., Latest research and treatment of advanced-stage epithelial ovarian cancer. Nat Rev Clin Oncol, 2013.10(4):p211-24. 18.Frank, T.S., et al., Sequence analysis of BRCA1 and BRCA2:correlation of mutations with family history and ovarian cancer risk. J Clin Oncol, 1998.16(7):p.2417-25. 19.Permuth, W. J., et al., Epidemiology of ovarian cance. Methods Mol Biol, 2009.472:p413-37. 20.Risch, H.A., et al., Hormonal etiology of epithelial ovarian cancer, with a hypothesis concerning the role of androgens and progesterone. J Natl Cancer Inst, 1998.90(23):p.1774-86. 21.Beehler, G.P., et al., Risk of ovarian cancer associated with BMI varies by menopausal status. J Nutr, 2006.136(11):p.2881-6. 22.Olsen, C.M., et al., Obesity and the risk of epithelial ovarian cancer: a systematic review and meta-analysis. Eur J Cancer, 2007.43(4):p.690-709. 23.Markman, M., et al., Impact of age on survival of patients with ovarian cancer. Gynecol Oncol, 1993.49(2):p.236-9. 24.Winter, W.E., et al., Prognostic factors for stage III epithelial ovarian cancer: a Gynecologic Oncology Group Study. J Clin Oncol, 2007.25(24):p.3621-7. 25.Ezzati, M., et al., Recent Advancements in Prognostic Factors of Epithelial Ovarian Carcinoma. Int Sch Res Notices, 2014:p.953509. 26.Hannibal, C.G., et al., A binary histologic grading system for ovarian serous carcinoma is an independent prognostic factor: a population-based study of 4317 women diagnosed in Denmark 1978-2006. Gynecol Oncol, 2012.125(3):p.655-60. 27.Sato, E., et al., Intraepithelial CD8+ tumor-infiltrating lymphocytes and a high CD8+/regulatory T cell ratio are associated with favorable prognosis in ovarian cancer. Proc Natl Acad Sci U S A, 2005.102(51):p.18538-43. 28.Graeff, P. de., et al., Modest effect of p53, EGFR and HER-2/neu on prognosis in epithelial ovarian cancer: a meta-analysis. Br J Cancer, 2009.101(1):p.149-59. 29.Makin, G. and Dive, C., Apoptosis and cancer chemotherapy. Trends Cell Biol, 2001.11(11):p.S22-6. 30.Kleef, J. and Ishiwata, T., The cell surface heparin sulfate proteoglycan glypican-1 regulates growth factor in pancreatic carcinoma cell and is overexpressed in human pancreatic cancer. J.Clin.Invest, 1998.102(9): p.1662–73. 31.Melo, S. A., et al., Glypican-1 identifies cancer exosomes and detects early pancreatic cancer. Nature, 2015.523(9): p.177-182. 32.Fang, F., et al., Expression of cyclophilin B is associated with malignant progression and regulation of genes implicated in the pathogenesis of breast cancer. Am J Pathol, 2009.174(1):p.297-308. 33.Price, E.R., et al., Human cyclophilin B: a second cyclophilin gene encodes a peptidyl-prolyl isomerase with a signal sequence. Proc Natl Acad Sci U S A, 1991.88(5):p.1903-1907. 34.Bast, R.J., et al., A radioimmunoassay using a monoclonal antibody to monitor the course of epithelial ovarian cancer. N Engl J Med, 1983.309(15): p.883–87. 35.Chang, K., et al., Isolation and characterization of a monoclonal antibody, K1, reactive with ovarian cancers and normal mesothelium. Int J Cancer, 1992. 50(3):p.373–81. 36.Chang, K. and Pastan, I., Molecular cloning of MSLN, a differentiation antigen present on mesothelium, mesotheliomas, and ovarian cancers. Proc Natl Acad Sci USA, 1996.93(1):p.136–40. 37.Argani, P., et al., Mesothelin is overexpressed in the vast majority of ductal adenocarcinomas of the pancreas: identification of a new pancreatic cancer marker by serial analysis of gene expression (SAGE). Clin Cancer Res, 2001.7(12):p.3862–68. 38.Hippo, Y., et al., Differential gene expression profiles of scirrhous gastric cancer cells with high metastatic potential to peritoneum or lymph nodes. Cancer Res, 2001.61(3):p.889–95. 39.Frierson, H.J., et al., Large-scale molecular and tissue microarray analysis of mesothelin expression in common human carcinomas. Hum Pathol, 2003.34(6):p. 605–09. 40.Hassan, R. and Pastan, I., Mesothelin : a new target for immunotherapy. Clin Cancer Res, 2004.10(12):p.3937–42. 41.Huang, C.Y., et al., Serum mesothelin in epithelial ovarian carcinoma: a new screening marker and prognostic factor. Anticancer Res, 2006.26(6):p.4721–28. 42.Chang, M.C., et al., Mesothelin inhibits paclitaxel-induced apoptosis through the PI3K pathway. Biochem J, 2009.424(3):p449-58. 43.Arber, S., et al., Regulation of actin dynamics through phosphorylation of cofilin by LIM-kinase. Nature, 1998.393(6687):p.805-09. 44.Yang, N., et al., Cofilin phosphorylation by LIM-kinase 1 and its role in Rac-mediated actin reorganization. Nature, 1998.393(6687):p.809-12. 45.Sumi, T., et al., Cofilin phosphorylation and actin cytoskeletal dynamics regulated by rho- and Cdc42-activated LIM-kinase 2. J Cell Biol, 1999.147(7):p.1519-32. 46.Maekawa, M., et al., Signaling from Rho to the actin cytoskeleton through protein kinases ROCK and LIM-kinase. Science, 1999.285(5429):p.895-8. 47.Dan, S., et al., An integrated database of chemosensitivity to 55 anticancer drugs and gene expression profiles of 39 human cancer cell lines. Cancer Res, 2002.62 (4):p.1139-47. 48.Yajnik, V., et al., DOCK4, a GTPase activator, is disrupted during tumorigenesis. Cell, 2003.112(5):p.673-84. 49.Fok, K.L., et al., STK31 maintains the undifferentiated state of colon cancer cells. Carcinogenesis, 2012.33(11):p.2044-53. 50.Yokoe, T., et al., Efficient identification of a novel cancer/testis antigen for immunotherapy using three-step microarray analysis. Cancer Res, 2008. 68(4):p.1074-82. 51.Zang, Z.J., et al., Genetic and structural variation in the gastric cancer kinome revealed through targeted deep sequencing. Cancer Res, 2001.71(1):p29-39. 52.Xia, J., et al., A meta-analysis of somatic mutations from next generation sequencing of 241 melanomas: a road map for the study of genes with potential clinical relevance. Mol Cancer Ther, 2014.13(7):p.1918-28. 53.Kuo, PL., et al., STK31 is a cell-cycle regulated protein that contributes to the tumorigenicity of epithelial cancer cells. PLoS One, 2014.9(3):e93303. 54.Rodon, J., et al., Early drug development of inhibitors of the insulin-like growth factor-I receptor pathway: lessons from the first clinical trials. Mol Cancer Ther, 2008.7(9):p.2575-88. 55.Playford, M.P., et al., Insulin-like growth factor 1 regulates the location, stability, and transcriptional activity of beta-catenin. Proc.Nat.Acad. Sci, 2000.97(22):p.12103-08. 56.Samani, A.A., et al., The role of the IGF system in cancer growth and metastasis: overview and recent insights. Endocr Rev, 2007.28(1):p.20-47. 57.Denduluri, SK., et al., Insulin-like growth factor (IGF) signaling in tumorigenesis and the development of cancer drug resistance. Genes & Diseases, 2015.2(1):p.13-25. 58.Johansen, J.S., et al., Plasma YKL-40: a potential new cancer biomarker? Future Oncol, 2009.5(7):p.1065–82. 59.Choudhuri, S., et al., A repertoire of biomarkers helps in detection and assessment of therapeutic response in epithelial ovarian cancer. Mol Cell Biochem, 2014. 386(1):p.259–69. 60.Dehn, H., et al., Plasma YKL-40, as a prognostic tumor marker in recurrent ovarian cancer. Acta Obstet Gynecol Scand, 2003.82(3):p.287–93. 61.Dupont, J., et al., Early detection and prognosis of ovarian cancer using serum YKL-40. J Clin Oncol, 2004.22(16):p.3330–39. 62.Gronlund, B., et al., Pretreatment prediction of chemoresistance in second-line chemotherapy of ovarian carcinoma: value of serological tumor marker determination (tetranectin, YKL-40, CASA, CA125). Int J Biol Markers, 2006. 21(3):p.141–48. 63.Hogdall, EV., et al., High plasma YKL-40 level in patients with ovarian cancer stage III is related to shorter survival. Oncol Rep, 2003.10(5):p.1535–38. 64.Hogdall, EV., et al., YKL-40 tissue expression and plasma levels in patients with ovarian cancer. BMC Cancer, 2009.9:p.8. 65.Yip, P., et al., Comprehensive serum profiling for the discovery of epithelial ovarian cancer biomarkers. PLoS One, 2011.6(12):e29533. 66.Wang, D., et al., High YKL-40 serum concentration is correlated with prognosis of Chinese patients with breast cancer. PLoS One, 2012.7(12):e51127. 67.Bernardi, D., et al., Serum YKL-40 following resection for cerebral glioblastoma. J Neurooncol, 2012.107(2):p.299–305. 68.Ambrosini, G., et al., Induction of apoptosis and inhibition of cell proliferation by survivin gene targeting. J Biol Chem, 1998.273(18):p.11177–82. 69.Li, F., et al., Control of apoptosis and mitotic spindle checkpoint by survivin. Nature, 1998.396(6711):p.580–4. 70.Ambmsini, G., et al., A novel antiapoptosis gene survivin expressed in cancer and lymphoma. Nat Med, 1997.3(8):p.917–21. 71.Weinman, E.C., et al., Characterization of antigen processing machinery and survivin expression in tonsillar squamous cell carcinoma. Cancer, 2003.97(9):p. 2203–11. 72.Shariat, SF., et al., Survivin expression is associated with features of biologically aggressive prostate carcinoma. Cancer, 2004.100(4):p.751–7. 73.Saxena, A., et al., Cellular response to chemotherapy and radiation in cervical cancer. Am J Obstet Gynecol, 2005.192(5):p.1399–403. 74.Muzio, LL., et al., Survivin expression in oral squamous cell carcinoma. Br J Cancer, 2003.89(12):p.2244–48. 75.Rodel, F., et al., Survivin as a radioresistance factor and prognostic and therapeutic target for radiotherapy in rectal cancer. Cancer Res, 2005.65(11):p. 4881–87. 76.Kami, K., et al., Survivin expression is a prognostic marker in pancreatic cancer patients. Surgery, 2004.136(2):p.443–8. 77.Lee, JP., et al., Survivin, a novel anti-apoptosis inhibitor, expression in uterine cervical cancer and relationship with prognostic factors. Int J Gynecol Cancer, 2005.15(2):p.113–9. 78.Fernandina, G., et al., Survivin expression in ovarian cancer and its correlation with clinicopathological, surgical and apoptosisrelated parameters. Br J Cancer, 2005.92(2):p.271–77. 79.Tringler, B., et al., Immunohistochemical localization of survivin in serous tumors of the ovary. Appl Immunohistochem Mol Morphol, 2004.12(1):p.40–3. 80.Kleinberg, L., et al., Nuclear expression of survivin is associated with improved survival in metastatic ovarian carcinoma. Cancer, 2007.109(2):p.228–38. 81.Cohen, C., et al., Survivin expression in ovarian carcinoma: correlation with apoptotic markers and prognosis. Mod Pathol, 2003.16(6):p.574–83 82.Kao, C.J., et al., CBAP interacts with the un-liganded common beta-subunit of the GM-CSF/IL-3/IL-5 receptor and induces apoptosis via mitochondrial dysfunction. Oncogene, 2008.27(10):p.1397-403. 83.Chiang, Y.J., et al., CBAP functions as a novel component in chemokine-induced ZAP70-mediated T-cell adhesion and migration. PLoS One, 2013.8(4):e61761. 84.Ho, K.C., et al., CBAP promotes thymocyte negative selection by facilitating T-cell receptor proximal signaling. Cell Death Dis, 2014.5:e1518. 85.Dranoff, G., Cytokines in cancer pathogenesis and cancer therapy. Nat Rev Cancer, 2004.4(1):p.11-22. 86.Chen, YL., et al., IL17a and IL21 combined with surgical status predict the outcome of ovarian cancer patients. Endocr Relat Cancer, 2015.22(5):p703-11 87.Kurman, RJ., et al., The origin and pathogenesis of epithelial ovarian cancer: a proposed unifying theory. Am J Surg Pathol, 2010.34(3):p433-43. 88.Wei, W., et al., Ovarian cancer: genomic analysis. Ann Oncol, 2013.24(10):p7-15. 89.Chiang, Y.C., et al., Overexpression of CHI3L1 is associated with chemoresistance and poor outcome of epithelial ovarian carcinoma. Oncotarget, 2015.6(37):p39740-55. 90.Zheng, H.C., et al., The molecular mechanisms of chemoresistance in cancers. Oncotarget, 2017.8(35):p59950-64. 91.Liu, X., et al., Oncogenes associated with drug resistance in ovarian cancer. J Cancer Res Clin Oncol, 2015.141(3):p381-95. | - |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/7545 | - |
dc.description.abstract | 本論文的研究目的是將卵巢癌病患分為兩個族群:化療敏感性(Chemo -sensitive)和化療抗藥性(Chemo - resistant),比較兩個族群間十個基因表現量的差異,以及利用計算風險分數(Risk score)和總體得分(Overall score),評估這樣的計分方式是否能夠作為預測卵巢上皮細胞癌的化療反應和預後之指標。
研究共收集149位卵巢癌病患的組織檢體,包含75位化療敏感性(Chemo -sensitive)的卵巢癌病患和74位化療抗藥性(Chemo - resistant)的卵巢癌病患,紀錄患者的臨床病理特徵,並利用即時定量聚合酶連鎖反應(Quantitative real-time polymerase chain reaction, QRT-PCR)偵測十個基因的表現量,十個基因包括: GPC1、CYPB、MSLN、LIMK2、DOCK4、STK31、IGF1、CHI3L1、Survivin、CBAP。另外,利用計算病患的風險分數(Risk score)和總體得分(Overall score)評估病患對於化療反應(Chemo-response)、疾病復發(Disease relapse)和存活狀況(Disease-related death)的相關性,最後進一步分析總體得分的高低與病患的五年無病存活期(Disease free survival, DFS)和整體存活期(Overall survival, OS)之關聯性。 研究結果顯示在化療抗藥性族群之10個基因表現量皆比化療敏感性族群高,並在病患的風險分數和總體得分的分析中,發現化療抗藥性族群的總體得分分佈要較化療敏感性族群高。驗證得到以總體得分的計分方式對於化療反應(Chemo-response)、疾病復發(Disease relapse)和存活狀況(Disease-related death)的 鑑別性是好的。也觀察到當總體得分高的時候,會有較差的無病存活期和整體存活期。 總體而言,應用總體得分的計分方式,當總體得分愈高,病患的預後愈差,因此,可以作為有發展潛能的生物指標,用來預測卵巢癌的化療反應和預後。 | zh_TW |
dc.description.abstract | The purpose of the study was to compare the genetic expression in ovarian cancer between chemo-sensitive and chemo-resistant groups. In addition, evaluating whether the scoring method calculating the risk score and overall score could be a biomarker of chemo-response and prognosis in ovarian cancer.
Total 147 ovarian cancer patients were enrolled in this study, including 75 patient of chemo-sensitive and 74 patients of chemo-resistant. We collected clinicopathological characteristics of patients and determined genetic expression by Quantitative real-time polymerase chain reaction (QRT-PCR).There are ten genes, including GPC1, CYPB, MSLN, LIMK2, DOCK4, STK31, IGF1, CHI3L1, Survivin, CBAP. In addition, evaluating correlations between chemo-response, disease relapse, and disease-related death by calculating the risk score and overall score. Then, we analyzed the relationship between overall score, disease free survival(DFS) and overall survival(OS) further. The genetic expression of patient in chemo-resistant group was higher than in chemo-sensitive group. The distribution of overall score was also higher in chemo- resistant group than in chemo-sensitive group. Good correlations between overall score, chemo-response, disease relapse, and disease-related death by scoring method. Patients with higher overall score had a shorter disease free survival(DFS) and overall survival(OS). These results suggest that the patients with higher overall score had worse clinical outcome. Therefore, scoring system for calculating the overall score of clinical risk evaluation shows potential to predict the chemo-response and outcome in ovarian cancer. | en |
dc.description.provenance | Made available in DSpace on 2021-05-19T17:46:05Z (GMT). No. of bitstreams: 1 ntu-107-P05448004-1.pdf: 1939275 bytes, checksum: 1300e2d49ed88aab1efac136a4cdf538 (MD5) Previous issue date: 2018 | en |
dc.description.tableofcontents | 目錄
口試委員會審定書...................i 致謝.............................ii 中文摘要.........................iii 英文摘要.........................iv 前言..............................1 材料與方法........................10 實驗結果..........................15 討論..............................24 參考文獻..........................30 表目錄 表一、卵巢癌病人臨床資料特徵..............................39 表二、十個卵巢癌相關基因在化療敏感組和化療抗藥組別基因表現量的差異......................................................40 表三、十個卵巢癌相關基因對於化療反應影響的風險程度..........41 表四、卵巢癌病人總體得分的分佈比例.........................42 表五、總體得分對於化療反應的最佳切點.......................43 表六、總體得分對於疾病復發的最佳切點.......................44 表七、總體得分對於存活狀況的最佳切點.......................45 表八、卵巢癌病人對於化療反應之預後因子分析.................46 表九、TCGA卵巢癌病人臨床資料特徵..........................47 圖目錄 圖一、十個基因及house-keeping gene的QRT-PCR代表圖.........48 圖二、化療敏感組和化療抗藥組別間總體得分的分布..............52 圖三、總體得分對於化療反應的ROC曲線........................53 圖四、總體得分對於疾病復發的ROC曲線........................54 圖五、總體得分對於存活狀況的ROC曲線........................55 圖六、卵巢癌病人五年的無病存活期...........................56 圖七、卵巢癌病人五年的整體存活期...........................57 圖八、達到最佳減積手術之卵巢癌病人五年的無病存活期..........58 圖九、達到最佳減積手術之卵巢癌病人五年的整體存活期..........59 圖十、未達到最佳減積手術之卵巢癌病人五年的無病存活期........60 圖十一、未達到最佳減積手術之卵巢癌病人五年的整體存活期.......61 圖十二、TCGA化療敏感組和化療抗藥組別間總體得分的分布........62 圖十三、TCGA卵巢癌病人的整體存活期........................63 | - |
dc.language.iso | zh_TW | - |
dc.title | 比較卵巢癌病患化療敏感性族群和化療抗藥性族群間的基因表現量差異 | zh_TW |
dc.title | Genetic expression in ovarian cancer : Comparison of chemo-sensitive and chemo-resistant groups | en |
dc.type | Thesis | - |
dc.date.schoolyear | 106-2 | - |
dc.description.degree | 碩士 | - |
dc.contributor.coadvisor | 鄭文芳 | zh_TW |
dc.contributor.coadvisor | Wen-Fang Cheng | en |
dc.contributor.oralexamcommittee | 陳宇立 | zh_TW |
dc.contributor.oralexamcommittee | Yu-Li Chen | en |
dc.subject.keyword | 卵巢癌,預後指標,化療敏感性,化療抗藥性,基因表現,風險分數,總體得分, | zh_TW |
dc.subject.keyword | ovarian cancer,prognostic biomarker,chemo-sensitive,chemo- resistant,genetic expression,risk score,overall score, | en |
dc.relation.page | 63 | - |
dc.identifier.doi | 10.6342/NTU201800914 | - |
dc.rights.note | 未授權 | - |
dc.date.accepted | 2018-07-27 | - |
dc.contributor.author-college | 醫學院 | - |
dc.contributor.author-dept | 分子醫學研究所 | - |
dc.date.embargo-lift | 2023-10-09 | - |
顯示於系所單位: | 分子醫學研究所 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-106-2.pdf 目前未授權公開取用 | 1.89 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。