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研究生: 王世宗
Shih-Tsung Wang
論文名稱: cDNA微陣列基因表現圖譜於肺癌化學治療敏感性預測之應用
Prediction of sensitivity of lung cancer to chemotherapy by cDNA microarray analysis of gene expression profiles
指導教授: 王憶卿
Wang, Yi-Ching
學位類別: 碩士
Master
系所名稱: 生命科學系
Department of Life Science
論文出版年: 2004
畢業學年度: 92
語文別: 英文
論文頁數: 96
中文關鍵詞: 肺癌抗藥性鉑帝爾cDNA微陣列分析技術即時聚合鏈反應
英文關鍵詞: lung cancer, drug resistance, cisplatin, cDNA microarray analysis, real-time PCR
論文種類: 學術論文
相關次數: 點閱:401下載:2
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  • 肺癌為國人癌症死亡首位的,肺癌病人通常在腫瘤切除後五年內死於癌症復發或腫瘤轉移。又大部分的病人對於化療會產生抗藥性(drug resistance)。一些和化療藥物的抗藥性有關的研究在癌症細胞模式已經獲得證實。尋找和抗藥性有關的基因為當前重要的課題。一些分子層次的研究已經證實抗藥性的形成是由於多個基因(genetic)和外基因(epigenetic)的變異所導致的結果,而不是因為單一基因的變異所形成的機制。傳統上利用單一基因或少數基因的分析實不足以瞭解癌症抗藥性的形成機轉。因此,此研究的目的利用含有13675點基因/表現基因標記(expressed sequence tags)的cDNA微陣列分析技術(cDNA microarray analysis),利用五株對鉑帝爾(cisplatin/cis-diamminedichloroplatinum)有不同抗藥性的程度的肺癌細胞株(lung cancer cell lines),包括H23、H1437、H226、H1355、H647以及H14345,分析他們在先天上基因表現圖普的差異,以找出和抗藥性有關的共同基因。此外,此研究也以鉑帝爾的半致死劑量(IC50)處理以上五株細胞中對於鉑帝爾分別具有最大抗藥性感與最敏感性的細胞株H1435以及H23,並分析在短暫處理完藥物後不同的時間點(4, 5, 6, 8, 12, 24小時)的基因表現圖普的差異。結果顯示,在五株細胞中,有33個基因的基因表現會隨著抗藥性的升高而上升;84個基因的基因表現會隨著抗藥性的升高而被抑制。另外在鉑帝爾處理的部分,表現差異在2、3和4倍以上的基因分別有656、218和96個。即時聚合鏈反應(real-time PCR)分析9個基因,其中有5基因和為陣列分析的結果達到顯著相關。此研究提供了一群和和抗藥性有關的基因,但是未來必須建立一套基因調節的網路。
    關鍵詞:肺癌、抗藥性、鉑帝爾、cDNA微陣列分析技術、即時聚合鏈反應

    The great majority of lung cancer patients relapse with tumor that is largely refractory to further chemotherapeutic treatment. Many genetic alterations associated with drug resistance of cell models have been verified in cancers, but the precise molecular mechanisms remain unclear. It is important to identify genes related to drug resistance. Investigators using various molecular approaches have suggested that multiple genetic and epigenetic changes might correlate with drug resistance. Therefore, the present study used the cDNA microarray with 13675 genes/expressed sequence tags to analyze the expression profiles of five cell lines including H226, H1437, H1355, H647, and H1435, which had known resistance to cisplatin, to identify the common drug resistance genes. In addition, cisplatin-resistant H1435 versus cisplatin-sensitive H23 lung cancer cell lines that were transiently treated with cisplatin at their IC50 doses for 0, 1, 2, 4, 8, 20 hours. The data indicated that overexpression of 33 genes was commonly correlated with gradual increase of resistance in these five lung cancer cell lines, whereas low expression of 84 genes was correlated with gradual decrease of resistance to these cell lines. In addition, there were 656, 218, and 96 genes that their gene expressions were up to 2, 3 and 4 fold in H1435 cisplatin-treated samples, respectively. The confirmation study which used real-time reverse-transcriptase polymerase chain reaction (RT-PCR) was carried out in 9 genes. It found a significant correlation of the gene expression changes for 5 genes of 9 genes. This study identified novel genes associated with cisplatin resistance. This kind of analysis should build gene-regulatory networks in near future.
    Key words:lung cancer、drug resistance、cisplatin、cDNA microarray analysis、real-time PCR

    Abstract----------------------------------------------------1 Introduction--------------------------------------------- 5 I. Mechanism of drug resistance in lung cancer----6 II. History and application of cDNA microarray---13 III. Application of cDNA microarray in drug resistance of cancer----------------------------------- 21 Purpose----------------------------------------------------- 26 Materials and Methods--------------------------------- 27 I. Cell lines and their culture--------------------------- 27 II. Cisplatin treatment in H23 and H1435----------- 27 III. RNA extraction----------------------------------------- 28 IV. Agilent human 1 cDNA microarray kits----------- 29 V. cDNA microarray process---------------------------- 29 Result-------------------------------------------------------- 38 I. Initial results using the Agilent human 1 cDNA microarray ----------------------------------------------38 II. Basal level------------------------------------------ 38 III. Induced level-------------------------------------------- 40 IV. Sequential model--------------------------------------- 41 V. Correlation between PCR and gene expression--43 Discussion-------------------------------------------------------44 I. Basal level---------------------------------------------------- 44 II. Induced level------------------------------------------ 44 III. Correlation between PCR and gene expression------ 45 IV. Sequential model------------------------------------- 46 Future work and application---------------------- 47 Reference-------------------------------------------------- 48 Figures------------------------------------------------------ 66 Tables------------------------------------------------------- 76 FIGURE CONTENT Figure 1. The Agilent chip over-view--------------------------------------- 66 Figure 2. Self-hybridization-------------------------------------------------- 67 Figure 3. Heat map and Kmeans cluster of 117 basal level genes-------68 Figure 4. Cellular component of 117 basal level genes------------------- 69 Figure 5. Biological process of 117 basal level genes-------------------- 70 Figure 6. Hierarchical cluster of 656 cisplatin responsive gens--------- 71 Figure 7. Cellular component of 218 cisplatin responsive genes ------- 72 Figure 8. Biological process of 218 cisplatin responsive genes--------- 73 Figure 9A. sequential model of paralleled correlation-------------------- 74 Figure 9B. sequential model of anti-paralleled correlation--------------- 74 TABEL CONTENT Tabel 1. IC50 of five lung cancer cell lines---------------------------------76 Tabel 2. The 117 selected differential expressed genes at the untreated basal level----------------------------------------- 77 Tabel 3. Responsive genes in H1435 to cisplatin-------------------------- 84 Tabel 4. Comparison between microarray and real-time PCR for the H1435 cisplatin treated samples------------------- 96

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