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系統識別號 U0026-2208201615452200
論文名稱(中文) 開發一種尿液診斷尿路上皮癌的新穎方法
論文名稱(英文) Develop a novel method for the urinary diagnosis of urothelial carcinoma
校院名稱 成功大學
系所名稱(中) 醫學檢驗生物技術學系
系所名稱(英) Department of Medical Laboratory Science and Biotechnology
學年度 104
學期 2
出版年 105
研究生(中文) 何怡慧
研究生(英文) Yi-Hui Ho
學號 T36034123
學位類別 碩士
語文別 英文
論文頁數 66頁
口試委員 指導教授-黃暉升
口試委員-謝淑珠
口試委員-蔡弘文
口試委員-彭淑玲
中文關鍵字 尿路上皮癌  生物標誌  靈敏度  柏氏染色 
英文關鍵字 Urothelial carcinoma  Papanicolaou stain  CellDetect®  biomarker  CDCP1 
學科別分類
中文摘要 尿路上皮癌(urothelial carcinoma, UC) 是世界上最致命的癌症之一,在美國男性中UC是第四名常見的癌症。UC主要可分為兩種類型: 肌肉侵犯型(T2-T4)及非肌肉侵犯型(Tis, Ta, T1),其中以非肌肉侵犯型UC佔大多數且復發率高達70%。因此,UC病人常需定期回診做追蹤檢測。臨床上,黃金標準診斷UC的方法為膀胱鏡。然而,膀胱鏡是屬於侵入性、昂貴及造成病人不舒服感的方法。其他非侵入性診斷方法包含尿液細胞學及生物標記檢測。目前尿液細胞學所使用的染色方法是Papanicolaou (Pap) stain,Pap stain擁有高特異性,但對於檢測低惡性UC的靈敏度卻相當低且需要專業的病理人員透過細胞型態及特性判定是否為癌細胞。在本篇的研究中,我們比較傳統染劑(Pap stain)及新穎染劑(CellDetect®)何者較適合臨床的使用,CellDetect®能經由顏色區分正常細胞及癌細胞以降低病理人員需透過專業知識判定癌細胞的負擔。在對照28位病人的組織切片中,我們發現CellDetect®的靈敏度、陽性預測值及陰性預測值較Pap stain為佳。我們提出CellDetect®結合自動化儀器利用顏色區分以偵測尿液的癌細胞,而這個自動化儀器將會提高診斷效率及降低臨床病理人員的負擔。另一方面,現今美國食品藥物管理局認可的生物標記對於臨床檢測UC的靈敏度及專一性仍不夠合適,因此我們想要開發一個具高專一性的生物標記檢測UC。近年來研究發現,CDCP1是第一型穿膜的醣蛋白,在許多癌症中都有過度表現的情形,包含肺癌、乳癌、大腸癌、腎臟癌等。在本篇研究中主要是探討CDCP1在UC的臨床意義及檢測的應用性。我們利用免疫組織化學染色分析CDCP1在91例尿路上皮組織陣列中的臨床角色及意義,結果顯示CDCP1在UC病人中有過度表現的情形且和腫瘤分化具有高度相關性,這意味著CDCP1可能成為尿液中檢測UC有用的生物標記。利用CDCP1免疫細胞染色中我們發現當尿液中含有至少五顆以上三價的癌細胞,此人有很大的機率為UC病人。我們認為將CDCP1應用在臨床尿液檢測上可改善診斷效率及減少侵入性膀胱鏡檢測的使用次數。
英文摘要 Urothelial carcinoma (UC) is one of the most fatal cancer in the world, and the American Cancer Society has reported that bladder cancer is the fourth most common cancer among men. UC includes two subtypes: muscle invasive urothelial carcinoma (MIUC; T2-T4) and non-muscle invasive urothelial carcinoma (NMIUC; Tis, Ta, T1). NMIUC occupies most of UC and has high recurrence rate of up to 70%. Therefore, NMIUC patients need regular surveillance. The gold standard of clinical diagnoses of UC is cystoscopy, which is an invasive and expensive method. The other diagnostic methods are non-invasive, including urinary cytology and biomarkers detection. Papanicolaou (Pap) stain is widely used in cytology with high specificity, but low sensitivity to detect low-grade UC and requirement of pathological experts to clarify malignant cells by their morphological characteristics. In the present study, we performed a novel cytological stain called CellDetect®, which could highlight malignant cells through their color discrimination. In comparison with the tissue biopsy of twenty-eight UC patients, the sensitivity, positive predictive value and negative predictive values of CellDetect® stain were better than those of Pap stain. We suggest that the CellDetect® stain might be a promising method to develop an automatic detector to screen urinary UC cells. It might promote the diagnostic efficiency and reduce the burden of pathologists. On the other hand, the sensitivity and specificity of urinary biomarkers, even though the FDA approved biomarkers, are not good for clinical detection so far. Thus, we wanted to develop a novel useful biomarker in the urinary detection of UC. CUB domain-containing protein 1 (CDCP1) is a type I transmembrane glycoprotein, which highly expresses in various cancers, such as lung, breast, colon, kidney cancers, etc. We evaluated tissue arrays containing 103 cases for expression of CDCP1 in tumors compared with normal urothelium tissues by IHC staining. The results showed that CDCP1 was overexpressed in UC patients and associated with tumor grade with highly statistical significance. It indicates that CDCP1 might be a useful biomarker in the urinary detection of UC. As we analyzed several cases of UC patients, we found out that if a patient had at least five trivalent malignant cells in CDCP1 IHC staining, the patient would cause higher probability of having UC. The applications of CDCP1 in urinary cytology of UC will improve the diagnostic efficiency of the method.
論文目次 Index

中文摘要 I
Abstract II
誌謝 IV
Index V
Contents VI
Abbreviations VII
List of Figures VIII
List of Tables IX
List of Appendix X


Contents

1. Introduction 1
2. Specific aims 8
3. Materials and methods 9
4. Results 26
5. Discussion 32
6. References 36
7. Figures 43
8. Tables 57
9. Appendix 63

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