2010-08-012024-05-13https://scholars.lib.ntu.edu.tw/handle/123456789/648758摘要：癌轉移為造成癌症病患死亡最重要的原因之ㄧ，也是目前癌症治療上很困難的一環，開發出針對癌轉移的新化合物或新治療策略為目前首要目標。本實驗室近期已建立以影像為基礎的高通量篩選系統平台，用以分析高轉移能力的癌細胞特徵，包括細胞侵襲性、血管新生、和腫瘤聚落形成能力等，而這分析平台能以NCI60 細胞株做為材料，進一步作為篩選工具，有效篩選上千種化合物，其中包含新穎的中藥之純化合物和已知的化合物，以及其它已應用在化學療法、標靶治療的藥物。NCI60 細胞株為目前體外篩選抗癌藥物最廣為使用的細胞株模式，但之前的篩選模式多半是以分析藥物對癌細胞株的細胞毒性為基礎，而非以特定細胞特徵分析。本計畫的目標為利用高通量篩選系統分析平台，篩選出對癌症惡性度的細胞特徵有抑制效果的化合物，並進一步以實驗證實篩選的結果。此外，我們可以進一步整合之前研究NCI60 的資料，包括已經建立的NCI60微陣列資料，以及對NCI60 細胞株基因表現(包括基因轉譯分析、微核醣核酸表現等)、細胞性狀(高通量篩選系統分析)、和藥物基因學分析的資料，不僅可以用來篩選出有潛力的標靶或相關的訊息傳遞路徑，也可以用來研究新開發化合物的藥理機制，並利用基因表現分析挑選出有效的癌症合併療法以抑制癌轉移。本計畫的優點在於能藉由電腦運算模式與藥物高通量篩選平台整合基因體相關資訊，尋找在癌轉移中的共同關鍵路徑及篩選有效抑制的化合物﹔亦或分析在不同癌症中針對不同癌轉移路徑而篩選不同的抑制藥物。本計畫將提供一個開發和分析抗癌轉移藥物的有效方法。<br> Abstract: Metastasis is the most important issue to cause cancer mortality and also a difficultchallenge for anti-cancer therapy. Developing new compounds or novel strategies foranti-metastasis has become an urgent mission. Recently, we setup the image-based highcontent analysis system and it will be applied in cancer metastasis-related phenotypingidentification, including migration, invasion, colony formation, and tube formationcapabilities. This system could be used effectively to screen thousands of compounds(including the novel herb compounds and the known compounds in chemotherapy, targettherapy, and other pharmacological effects) in the drug developing tool, the NCI60 cell lines.The NCI60 has been widely used for anti-cancer drug development for several years;however, most of the previous screenings were based on the cytotoxicity in these cancer celllines, not by the specific phenotype characters. In this project, we will focus on screening theeffective compounds by the metastasis-related phenotyping evaluation and several hits mightbe found and will be confirmed and validated. Furthermore, by integrating the publisheddatabases and our genomics (transcriptomics and microRNA profiles), cytomics(image-based high content analysis), and pharmacogenomic approaches in the NCI60 cellline, the data-based computational system will be helpful, not only in discovering thepossible targets or associated pathways for drug screening, but also useful to identify thepharmacological mechanism of new leading compounds and providing the genomic profilingto select the effective combination of treatments in anti-cancer metastasis, synergistically.The characteristic advantage of this project is trying to discover the common pathways, if itis exist and its specific inhibitors in cancer metastasis; if there is no such common pathways,we will try to find the different compounds for the different metastasis pathways in differentcancer types. This project provides the solution to develop the leading compound inanti-cancer metastasis efficiently.Brearst cancerColorectal cancerLeukemiaPancreatic cancer