臺灣博碩士論文加值系統

婦癌的臨床症狀在早期並不明顯且不易檢測，且其中的卵巢癌死亡率高，所以早期的診斷與治療是目前對抗婦癌最有效的方法。目前主要的癌症分期方法及評估復原的機會，分別是利用組織染色判斷及配合臨床診斷經驗，由於不確定性高，現存診斷方式仍有很大的改善空間。
利用奈米技術，開發一個新穎檢測平台，以快速診斷卵巢癌、子宮內膜癌的臨床期數以及增強對復原機會結果的評估，將有助於大幅提高對於婦癌的診斷精確性與治療用藥正確性。
我們收集臨床上不同期數的卵巢癌及子宮內膜癌檢體，將其檢體細胞分離，做初代培養後，培養在不同大小的奈米陣列上，經由CA125染色確認卵巢癌細胞，接著利用掃瞄式電子顯微鏡(SEM)及免疫染色方法觀察細胞在奈米陣列平台上的存活率、貼附能力、骨架生長情形及貼附面積，加以統計分析之後，建立一整套癌細胞行為分析資料庫。
實驗結果顯示，經由掃描式電子顯微鏡及免疫染色觀察發現婦癌細胞會因為不同奈米尺寸在各個期數下有不一樣的細胞反應，經過統計後，針對漿液型(serous type)卵巢癌細胞可利用50-nm 奈米點陣列進行存活率檢測判定期數，此外利用100-nm和300-nm奈米點陣列進行細胞面積和貼附能力的檢測判定級數；針對透明細胞型(clear cell type)卵巢癌細胞的評估， 50-nm 和100-nm 的奈米點陣列皆可作為存活率檢測判定期數，此外可利用100-nm和10-nm奈米點陣列進行細胞面積和貼附能力的檢測判定級數。綜合全部型態的卵巢癌細胞，可利用300-nm和10-nm的奈米點陣列進行細胞面積檢測判定期數和級數。子宮內膜癌可利用300-nm進行細胞骨架生長檢測判定期數以及利用300-nm、100-nm 和50-nm 分別進行細胞面積、貼附能力和細胞骨架檢測判定級數。比較各卵巢癌細胞在奈米點陣列上的行為表現與該臨床病人診療後復原狀況，我們發現診療後持續惡化的卵巢癌病人相較於診療後回復良好的病人，其癌細胞在奈米點陣列上具有較好的存活率，而在癌細胞面積與骨架生長方面，有七成的診療後持續惡化的卵巢癌病人其癌細胞在奈米點陣列上貼附面積較小且生成較少的骨架。因此，我們可以利用不同尺寸的奈米點陣列搭配不同的檢測方法對病人臨床期數、級數以及復原機會的評估進行體外分析與判定。期望可以利用奈米點陣列做為未來臨床癌症期數與級數的一個快速診斷平台，同時提供臨床病人診療後恢復率的評估。

Gynecologic cancer is a clinically typical female cancer, usually has a poor prognosis. It is deadly because it lacks any clear early detection or screening test. Therefore, early detection of cancer provides the best opportunity for successful management. The diagnosis and prognosis of cancer is evaluated by cancer spreading, tissue staining and with the clinical database experience. The universally accepted prognostic factors for patients are stage, grade and volume of residual disease. But this method are still considered preliminary, large uncertainty still exists in the existing diagnostic methods, there is still much room for improvement. In this study, we established a novel platform that can be used to assess basic parameters of cell response for the rapid diagnosis of gynecologic cancer clinical stages, and enhance the assessment of prognosis. We collected the different stages of clinical ovarian cancer and endometrioid adenocarcinoma (EMCA) specimens which isolated from tumor tissues or ascites. Cancer cells were cultured on different sizes of nanodot arrays. CA125 staining was used to confirm the MUC16 expression of ovarian cancer cells. We observed the cell viability, adhesion, cytoskeletal organization, and cell area by scanning electron microscopy (SEM) and immunostaining to establish a database for cancer cell behavior.
These SEM and immunostaining images result shows that there were different cell responses with different nanodot arrays in each clinical stage. After statistics, serous type of ovarian cancer could diagnose stages used cell viability methods on 50-nm nanodot array and could diagnose grades used cell area and focal adhesions methods on 100-nm and 300-nm nanodot arrays. Clear cell type of ovarian cancer could diagnose stages used cell viability method on 50-nm and 100-nm nanodot arrays and could diagnose grades used cell area and focal adhesions methods on 10-nm and 100-nm nanodot arrays. Above all ovarian cancer could diagnose stages and grades used cell area method on 10-nm and 300-nm nanodot arrays. EMCA could diagnose stages used actin filment method on 300-nm nanodot array and could diagnose grades used cell area, focal adhesions and actin filment methods on 300-nm, 100-nm and 50-nm nanodot arrays. In the prognosis results, we found above 70 % primary cancer cells revealed positive viability expression on poor prognosis patients compared to good prognosis patients. In cell attachment, both vinculin and actin revealed negative expression on poor prognosis patients compared to good prognosis patients. Therefore, we can evaluate clinical stages and prognosis of gynecologic cancer patients by using different nanodot arrays with various cell detections. We expected that the nanodot arrays can be used not only as the clinical stage of a rapid diagnostic platform, but also provide method for assessment of the clinical prognosis of gynecologic cancer patients in vitro.

CHAPTER 1: INTRODUCTION 1
CHAPTER 2: MATERIALS AND METHODS 6
2.1 ISOLATION AND CULTURE OF OVARIAN CANCER AND EMCA CELLS 6
2.2 CHEMICALS 7
2.3 FABRICATION OF THE NANODEVICE OF NANODOT ARRAYS 7
2.4 MORPHOLOGICAL OBSERVATION BY SCANNING ELECTRON MICROSCOPY (SEM) 8
2.6 DEFINITION OF GROWTH INDICES 10
2.7 STATISTICS 13
CHAPTER 3: RESULTS AND DISCUSSION 13
3.1 FABRICATION OF AN INTEGRATED NANODOT ARRAY DEVICE 13
3.2 CLINICALPATHOLOGIC SURVEY OF THE GYNECOLOGIC CANCER 14
3.3 IDENTIFICATION OF OVARIAN CANCER BY CA-125 IMMUNOSTAINING 16
3.4 NANODOT ARRAYS MODULATED GYNECOLOGIC CANCER CELLS MORPHOLOGY 18
3.5 NANODOT ARRAYS MODULATED CELL ADHESION AND CYTOSKELETON OF GYNECOLOGIC CANCER CELLS 23
3.6 TRENDS OF GYNECOLOGIC CANCER CELL BEHAVIORS 28
3.7 VD50, CAD50, FD50, AND CD50 SCORES OF GYNECOLOGIC CANCER CELLS. 34
3.8 CORRELATION OF GYNECOLOGIC CANCER CELLS BETWEEN CLINICAL STAGE AND NANODOT ARRAYS 37
3.9 PROGNOSTIC SURVEY OF OVARIAN CANCER BETWEEN CLINICAL STAGE AND DIFFERENT NANODOT ARRAYS 48
CHAPTER 4: CONCLUSIONS 52
REFERENCE 53

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