於痰液及血漿樣本中檢測遺傳和表遺傳生物分子指標做為肺癌早期
診斷依據的探討
Genetic and epigenetic biomarkers in sputum and plasma samples for early diagnosis of lung cancer
中文摘要
研究緣起：肺癌是國人癌症致死率的首位，也是全世界最普遍的惡性腫瘤之一，
全世界每年有超過百萬人死於肺癌，據統計罹患肺癌後五年的存活機率約 10~15%，依據患者手術當時的癌症分期而定，愈晚期治療，存活率愈低。傳統
上針對長期抽煙的人採用胸部X 光照影以及痰液細胞學檢驗來進行篩選的策
略，已經證實無法有效早期偵測肺癌來降低肺癌的致死率。因此利用靈敏性較高 的分子指標進行早期偵測是目前刻不容緩，也是提高肺癌患者存活率的重要工 作。
研究目的：癌細胞的轉變是一連串分子變異累積形成的，這些變異發生在抑癌基 因 (Tumor suppressor gene, TSG)、致癌基因 (Oncogene)、DNA 修補基因，以及 內在或外在環境因子造成的基因不穩定現象。已有少數研究顯示在肺癌病人痰 液、氣管灌流液以及血清樣本中，可以偵測出癌症相關基因啟動子高度甲基化、
基因座缺失及微衛星序列重複次數改變所得之基因體不穩定現象。本研究主要目 的在於更進一步確認可在肺癌患者的痰液(sputum) 及血漿(plasma)樣本中偵測 到與肺癌組織一致的分子變異指標，進一步挑選出多個靈敏性與專一性較高的分 子指標作為未來早期肺癌相關分子指標群 (Early detection biomarkers)。
研究方法：Part I，在 83 位肺癌病人的肺癌細胞及痰液 (sputum) 樣本中，利用 methylation-specific PCR (MSP) 共檢查了三個基因 (FHIT, p16INK4a, and RAR β) 的啟動子高度甲基化 (promoter hypermethylation)，並且偵測了八個微衛星序 列 (D3S1234, D3S1285, D5S1456, D9S286, D9S942, GATA49D12, D13S170, and D17S786) 的異質性缺失 (loss of heterozygosity, LOH) 及微衛星不穩定現象 (microsatellite instability, MSI)。Part II，63 位肺癌病人的肺癌組織及血漿 (plasma) 樣本中，利用MSP 共檢查了六個基因 (BLU, CDH13, FHIT, p16INK4a, RARβ, and RASSF1A) 的啟動子高度甲基化，並利用比色分析肺癌病人的血漿樣本之 DNA 總濃度。另外還有 36 位無肺癌個體的痰液及血漿樣本的偵測，分別作為肺 癌病人的痰液及血漿分析的對照組。
研究結果：Part I 痰液分析，本研究於肺癌細胞及痰液的分子指標偵測結果分別 進行靈敏性 (sensitivity)、專一性 (specificity)、一致性 (concordance) 及危險比 (odds ratio, OR) 的分析，挑選出的合適指標包括 D9S286、D9S942、GATA49D12、
D13S170 的 LOH，D9S942 MSI，以及 p16INK4a、RARβ的甲基化分析共七個 變異；其中，痰液樣本中發生D9S942 LOH 的危險比為 5.6 (95% confidence interval,
CI: 1.78~19.46, P=0.003)，p16INK4a 甲基化的危險比為 4.15 (95% CI: 1.46~15.02, P=0.006)。七個合適指標偵測結果採取聯集判定，其預測的靈敏度為 80%，專一
性有72%，一致性為 77%，未來將以此方式應用於早期肺癌的臨床檢驗。
Part II 血漿分析，甲基化頻率較高的指標有 p16INK4a、RARβ及 RASSF1A，且 血漿中p16INK4a 甲基化的危險比為 6.18 (95%CI: 1.89~28.0, P=0.002)，RASSF1A 甲基化的危險比為6.02 (95%CI: 1.82~27.52, P=0.002)。以 p16INK4a、RARβ以
及RASSF1A 三基因任一個甲基化的聯集判定，預測效果的靈敏度為 74%，專一
性有78%，一致性為 75%。利用 training set (43 位肺癌病人，22 位無肺癌個體) 的 偵測結果進行迴歸分析，再以test set (20 位肺癌病人 14 位無肺癌個體) 進行驗 證，得到82%的符合率，最後以所有樣本 (63 位肺癌病人，36 位無肺癌個體) 的 偵測結果計算得到的新迴歸方程式如下Y = -0.35＋0.30 (BLU methyl)＋1.84 (p16INK4a methyl)＋1.70 (RASSF1A methyl)，預測的靈敏性有 77%，專一性為 90%，一致性有 79%，未來將以此方式應用於早期肺癌的臨床檢驗。在血漿游離 DNA 總濃度測定方面，肺癌病人血漿 DNA 總濃度的中位數是 63.47ng/μl，無 癌症個體的血漿DNA 總濃度的中位數是 38.50 ng/μl，肺癌病人血漿 DNA 總濃 度高於無癌症個體的血漿DNA 總濃度 (P<0.0001)。且血漿 DNA 總濃度大於 cut-off 值 (50ng/μl)而罹患肺癌的危險比 3.42 (95% CI＝1.47~8.25, P=0.004)。
結論：分析結果所挑選出來的肺癌相關分子指標群，如：痰液中的七個微衛星和
甲基化指標群、血漿中的DNA 總濃度，未來將應用於臨床大量篩檢，檢查結果
為異常的個案將持續追蹤，期待能夠早期發現，早期治療，降低國人的肺癌致死 機率。
英文摘要
Purpose: Lung cancer is the leading cause of cancer deaths in Taiwan. Traditional radiography and sputum cytology have not been successfully reducing lung cancer mortality. It’s urgent to develop high sensitive molecular marker panel for large early lung cancer screening.
Strategy: Carcinogenesis is a multi-step process resulting from the accumulation of errors in vital regulatory pathways. The present study was designed to select multiple DNA markers, which have high sensitivity and specificity to serve as diagnostic biomarkers for lung cancer detection.
Methods: Part I, we examined the promoter hypermethylation of three tumor
suppressor genes (FHIT, p16INK4a, and RARβ) by methylation-specific PCR (MSP), and the instability of eight microsatellite markers (D3S1234, D3S1285, D5S1456, D9S286, D9S942, GATA49D12, D13S170, and D17S786) by loss of heterozygosity (LOH) and microsatellite instability (MSI) analyses in lung tumor cells and matched sputum specimens from 83 lung cancer patients. Part II, we examined the promoter hypermethylation of six tumor suppressor genes (BLU, CDH13, FHIT, p16INK4a,
RARβ, and RASSF1A) by MSP assay in lung tumor tissues and matched plasma specimens from 63 lung cancer patients. In addition, the DNA concentration in plasma was tested in 63 lung cancer patients and 36 cancer-free individuals. The 36
cancer-free individuals were also used as the negative control of part I study.
Results: Part I sputum study, based on the results of sensitivity, specificity, and concordance from each marker analyzed, we selected seven biomarkers, which were LOH of D9S286, D9S942, GATA49D12, and D13S170, MSI of D9S942, and methylation of p16INK4a and RARβ. In addition, the odds ratio of D9S942 LOH in sputum was 5.6 (95% confidence interval, CI: 1.78~19.46, P=0.003), and the odds ratio of p16INK4a methylation in sputum was 4.15 (95% CI: 1.46~15.02, P=0.006).
Using a definition that patient with cancer risk had alteration in more than two among seven selected biomarkers, we achieved a sensitivity of 80%, a specificity of 72%, and a concordance of 77%.
Part II plasma study, p16INK4a, RARβ, and RASSF1A genes had higher promoter hypermethylation frequencies. In addition, the odds ratio of p16INK4a methylation and RASSF1A methylation in plasma was 6.18 (95%CI: 1.89~28.0, P=0.002) and 6.02 (95% CI: 1.82~27.52, P=0.002), respectively. Using a definition of risk
individual showing alteration in more than one of the three selected biomarkers, we achieved a sensitivity of 74%, a specificity of 78%, and a concordance of 75%. The regression model calculated from the training set (43 cancer patients, 22 cancer-free individuals) had a match score of 82% comparing to the test set (20 cancer patients, 14 cancer-free individuals). The new regression model Y =0.35＋0.30 (BLU methyl)
＋1.84(p16INK4a methyl)＋1.70 (RASSF1A methyl), which calculated by overall cases (63 cancer patients, 36 cancer-free individuals), achieved a sensitivity of 77%, a specificity of 90%, and a concordance of 79%. In addition, the DNA concentration of plasma showed that the median DNA concentration of lung cancer patients
(63.47ng/μl) was significantly higher than cancer-free individuals (38.50ng/μl)
(P<0.0001). When the cut-off value was defined as 50 ng/μl of the DNA concentration in plasma, we achieved a sensitivity of 71% and a specificity of 61%. Additionally, the odds ratio of the DNA concentration in plasma determined by this cut-off value was 3.42 (95%CI: 1.47~8.25, P=0.004).
Conclusion: These selected early-etiologically associated biomarkers such as the seven selected LOH and methylation markers in spututm and DNA concentration in plasma can potentially be tested as supplement biomarkers for early lung cancer detection in the future.
