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研究生:張煜杰
研究生(外文):Yi-Chien Chang
論文名稱:以分類分析探討與檳榔相關之口腔癌基因異常
論文名稱(外文):Using classification analysis to investigate the gene alteration in the betel-associated oral carcinomas
指導教授:高材高材引用關係張國威
指導教授(外文):Tsair KaoKuo-Wei Chang
學位類別:碩士
校院名稱:國立陽明大學
系所名稱:醫學工程研究所
學門:工程學門
學類:生醫工程學類
論文種類:學術論文
論文出版年:2004
畢業學年度:92
語文別:中文
論文頁數:82
中文關鍵詞:口腔癌微陣列檳榔資料探勘分類
外文關鍵詞:oral cancermicroarraybeteldata miningclassification
相關次數:
  • 被引用被引用:3
  • 點閱點閱:163
  • 評分評分:
  • 下載下載:36
  • 收藏至我的研究室書目清單書目收藏:0
嚼食檳榔為台灣與東南亞等國家的特有社會現象。流行病學的統計研究發現嚼食檳榔與口腔癌有著高度的關聯,世界衛生組織也將其列為致癌物質之一。但在生化研究上,其致癌的機轉至今仍然未完全明朗。近來的研究發現癌症的發生可能為一連串基因突變所造成。為了研究其中嚼食檳榔對於基因的影響,以進一步分析其致癌的機制,將由口腔癌病患取得之樣本以微陣列(microarray)中的array-CGH 技術,偵測樣本中基因的拷貝數變異。我們再利用資料探勘(data mining)中的縮小重心分類法(shrunken centroids classifier)加以修改後進行分類分析(classification),藉此分析樣本中的「檳榔導致之口腔癌」與「其他口因素導致之口腔癌」此二類別的差異。分類法建立的模型成功的將樣本分類至正確的類別中,並找出28個在不同類別中表現具有差異的基因,包含FHIT、ERBB2、CDKN1B等基因,其中有些基因已有文獻探討其與口腔癌的關係,有些基因異常則未曾被報導過。而這些基因即可能與檳榔導致癌症有所相關。為了驗證分類模型的可信度,採用一次移除一個交互驗證來分析,而其結果也將大部分的樣本分類至正確的類別當中。在本研究中,我們展現了以分類法探討微陣列數據的應用潛力,也挑選出了數個顯著基因供更進一步的分析研究其機轉。
Chewing betel nuts is an addictive and unhealthy common habit in Taiwan society. Previous reports showed that chewing betel nuts is strongly associated with the high incidence of oral squamous cell carcinoma (OSCC) in Taiwan and adjacent Southeast Asian countries. However the genetic mechanism of OSCC is still not fully understood. In order to find out the differential gene alteration between betel-associated OSCC and OSCC induced by other factor, this study used a modified ‘shrunken centroid classifier’ to analyze the array CGH data to dissect the genetic variation between this two subtypes of OSCC. The method correctly classifies all samples and identifies the genes most relevant to the classification. Several of these genes have been reported in OSCC, but some genes alteration were novel identification in OSCC. To test the ability of classification model, the leave-one-out cross-validate and the model correctly employed classifies most of the samples. This study demonstrates the potential application of microarray classification analysis in classifying gene alteration in tumors. It will be useful in identifying gene significantly contributive for disease formation in future research.
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