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系統識別號 U0007-1807201116290100
論文名稱(中文) 於接受Cisplatin或Carboplatin治療之肺癌病人 運用基因及非基因因子進行療效及血液毒性之多元分析
論文名稱(英文) Multiple Analytical Approaches Demonstrate a Complex Relationship of Genetic and Non-Genetic Factors with Response and Hematological Toxicity to Cisplatin- or Carboplatin-Based Chemotherapy in Lung Cancer Patients
校院名稱 臺北醫學大學
系所名稱(中) 藥學研究所
系所名稱(英) Graduate Institute of Pharmacy
學年度 99
學期 2
出版年 100
研究生(中文) 劉世傑
研究生(英文) Shih-Chieh Liu
學號 M301098001
學位類別 碩士
語文別 中文
口試日期 2011-06-24
論文頁數 80頁
口試委員 共同指導教授-陳香吟
指導教授-劉興璟
委員-黃文鴻
委員-劉景平
委員-方嘉佑
中文關鍵字 鉑類藥物  基因多型性  療效  血液毒性 
英文關鍵字 platinum drugs  polymorphism  response  hematological toxicity 
學科別分類
中文摘要 根據行政院衛生署至民國九十七年之統計,肺癌已成為台灣癌症十大死因之首1。而於肺癌病人之治療藥物中,cisplatin與carboplatin為非小細胞肺癌之第一線治療藥物,但其治療反應率(response rate)僅約40%,而年存活率(one-year survival約為30%-40%2,3。同時,cisplatin與carboplatin會引起相關副作用之產生,如骨髓抑制毒性、噁心嘔吐、或神經毒性等。因此,如何增進病人療效與避免相關副作用之產生已為重要之課題。
本研究為回溯性研究,收錄116位使用cisplatin與carboplatin治療之肺癌病人。同時檢測其7種基因中的11項基因多型性,包含GSTP1 A313G、P53 G215C、UGT1A7 T387G、UGT1A7 T622C、NAT2 T481C、NAT2 G590A、NAT2 G857A、ERCC1 C118T、ERCC1 C8092A、ERCC4 T2247C與NQO1 C609T,並收集病人相關臨床數據,利用邏輯回歸與多因子降維法分析基因多型性與cisplatin及carboplatin治療之療效及血液毒性之關聯性。同時建立預測模型,藉以預測病人之療效與血液毒性之發生。
於療效分析中,UGT1A7低活性之基因型顯示具有較好之療效反應[OR=0.160 (0.027-0.952),P=0.044]。而於多因子降維法之分析中,UGT1A7, NAT2, NQO1 C609T與ERCC1 C118T為預測療效之最佳組合,評分量表ROC curve (Receiver Operating Characteristic curve) 之AUC (Area Under the Curve) 值為0.764。於血液毒性之分析中,NQO1 C609T CT之基因型產生較少血液毒性[OR=0.213 (0.053-0.848),P=0.028]。藉由多因子降維法推測NQO1 C609T, UGT1A7 與 ERCC1 C8092A為預測血液毒性之最佳組合。評分量表ROC curve之AUC值為0.656。
由結果推測UGT1A7與NQO1 C609T分別對於cisplatin 或carboplatin治療之療效及血液毒性具有影響。而於療效及血液毒性之預測模型中均顯示,僅考量單一因子預測力不高,須同時考量基因因子與非基因因子才會使預測率更加準確。
英文摘要 Introduction
Lung cancer is the leading cause of cancer-related death in Taiwan1. Patients with lung cancer are mostly treated with cisplatin- or carboplatin-based chemotherapy. However, the development of chemoresistance and the adverse toxicities, which might be affected by genetic polymorphisms or other non-genetic factors, has become the limitations in the treatments4,5. Therefore, the purpose of this study is to evaluate and to build a predictive model of the genetic polymorphisms that may impact treatment outcome of cisplatin- or carboplatin-based chemotherapy in lung cancer patients.
Patients and Methods
In this retrospective study, 116 lung cancer patients who received cisplatin or carboplatin chemotherapy in Wanfang hospital from 2005 to March, 2011 were genotyped for 11 polymorphisms in 7 genes (GSTP1 A313G, P53 G215C, UGT1A7 T387G, UGT1A7 T622C, NAT2 T481C, NAT2 G590A, NAT2 G857A, ERCC1 C118T, ERCC1 C8092A, ERCC4 T2247C and NQO1 C609T). The clinical response and the hematological adverse events were collected to evaluate the association between genetic polymorphisms and the clinical outcomes. Meanwhile, the scoring system and MDR (Multifactor Dimensionality Reduction) were used to evaluate the complex interaction between genetic and nongenetic factors.
Results
In the response analysis, the low activity homozygous UGT1A7 polymorphisms showed a better response rate (35%) compared to the wild type [13%; OR=0.160 (0.027-0.952),P=0.044]. Combining UGT1A7, NAT2, NQO1 C609T and ERCC1 C118T was the best to predict the response. The AUC (Area Under the Curve) of ROC curve (Receiver Operating Characteristic curve) was 0.764 in the risk score model. In the hematological toxicity analysis, the heterozygote of NQO1 C609T with less toxicity compared to the wild type [64% and 84%, respectively, OR=0.213 (0.053-0.848), P=0.028]. NQO1 C609T, UGT1A7 and ERCC1 C8092A showed as the best combination to predict the hematological toxicity. The AUC of ROC curve was 0.656 in the risk score model.
Conclusion
The results show that the UGT1A7 and NQO1 C609T polymorphisms might affect the response and the hematological toxicity of cisplatin or carboplatin-based chemotherapy. Considering both genetic and non-genetic factors can provide the better predictive ability in the risk score model.
論文目次 目錄
第一章 緒論 1
第二章 文獻探討 2
2.1 Cisplatin與Carboplatin簡介 2
2.1.1 Cisplatin與Carboplatin作用機轉 2
2.1.2 Cisplatin與Carboplatin之藥物動力學 3
2.1.2.1分布 3
2.1.2.2代謝 3
2.1.2.3排泄 3
2.1.3 Cisplatin與Carboplatin於癌症中之治療角色 4
2.1.4 Cisplatin與Carboplatin所引起之副作用 5
2.1.4.1骨髓抑制 5
2.1.4.2腎毒性 6
2.1.4.3神經毒性 6
2.1.4.4噁心嘔吐 7
2.2影響cisplatin與carboplatin療效與毒性之基因多型性 8
2.2.1藥物運輸蛋白之基因多型性 8
2.2.2 DNA損傷修復酵素之基因多型性 9
2.2.3藥物代謝與解毒之基因多型性 11
2.2.3.1 GSTP1基因多型性 11
2.2.3.2 NQO1基因多型性 11
2.2.3.3 NAT2基因多型性 12
2.2.3.4 UGT1A7基因多型性 14
2.2.4影響細胞凋亡之基因多型性 15
2.3基因多型性與癌症研究之現況及統計方式探討 15
2.3.1 多因子降維法 (Multifactor Dimensionality Reduction-MDR) 簡介 18
第三章 研究目的 21
第四章 研究方法 22
4.1研究設計 22
4.2研究對象 22
4.2.1 研究納入條件 22
4.2.2 研究排除條件 22
4.3資料收集與相關定義 23
4.3.1資料收集 23
4.3.2研究相關定義 23
4.4基因型檢測 24
4.4.1 DNA萃取流程 25
4.4.2 基因型之檢測-高效能液相層析儀(DHPLC) 25
4.4.3 基因型之檢測-TaqMan SNP Genotyping Assay 27
4.4.4基因型之檢測-限制?﹞螺峇軉q長度多型性(PCR-RFLP) 30
4.4.5質體DNA之製備 33
4.5統計方法 36
第五章 研究結果 37
5.1基因型分布-Hardy-Weinberg Equilibrium 分析 37
5.2療效與基本資料分析 39
5.2.1療效與基因多型性之分析 41
5.2.1.1療效與單基因Logistic Regression分析- 41
5.2.1.2療效與多因子降維法分析 43
5.2.1.3 The Framingham Study risk score 評分量表分析 44
5.3血液毒性與基本資料分析 49
5.3.2血液毒性與基因多型性之分析 51
5.3.2.1血液毒性與單基因Logistic Regression分析 51
5.3.2.2血液毒性與多因子降維法分析 53
5.3.2.3 The Framingham Study risk score評分量表分析 54
第六章 討論 58
6.1研究結果討論 58
6.1.1基因型頻率分布比較 58
6.1.2療效與基因多型性之關聯性 60
6.1.3血液毒性與基因多型性之關聯性 64
6.2研究限制與改進方向 68
第七章 結論 69

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