微型核醣核酸表現之微陣列分析和預測慢性B型肝炎病患罹患肝細胞癌

Microarray Analysis of MicroRNA Expression for Prediction of Hepatocellular Carcinoma in Chronic Hepatitis B Patients

連玉惠(Yu-Huei Lien)

指導教授 ： 于明暉

國立臺灣大學/公共衛生學院/流行病學與預防醫學研究所/碩士(2013年)

https://doi.org/10.6342/NTU.2013.10954

摘要

研究背景與目的：過去研究已經指出microRNAs (miRNAs) 透過使癌症相關基因的表現失去調節，參與癌症的形成與細胞分化。此外，從不同組織來的miRNAs可以在週邊血液裡被偵測到。因此，miRNAs具有成為應用在癌症診斷或篩檢介入之生物標記的潛力。本篇研究的目的在於從B型肝炎 (hepatitis B virus, HBV) 帶原者中找出HCC發展相關的特定循環miRNAs，並且探討這些miRNAs作為預測HCC風險之可信賴的新生物標記的可能性。
材料與方法：本篇研究使用巢式病例對照研究 (nested case - control study)，樣本源自於先前已經發表的世代研究。此世代研究在1989-1992年納入2903名HBV帶原者，並且持續追蹤這些研究對象至2009年。病例在以進入研究時間、進入研究年齡以及抽血時間點配對後，再隨機選取出本研究的對照組。本研究分成三個部分：(1) 使用微矩陣分析 (microarray analysis) 比較50名病例與50名對照之miRNAs表現差異，並且以Conditional logistic regression檢定；(2) 以miRNAs的表現為基礎執行路徑分析，以了解其生物上的意義；(3) 使用顯著的miRNAs指標建構HCC風險之預測模式。
結果：我們的微矩陣分析結果顯示79個顯著差異表現於病例和對照組的miRNAs，其中7個miRNAs在3端未轉譯區域預測的結合位置之基因 (miR-191、 miR-193a-3p、miR-23b、miR-3139、 miR-378f、miR-4640-5p以及miR-637) 參與ERK/MAPK、胰島素接受器 (insulin receptor)、mTOR、PI3K/AKT或者Wnt/β-catenin訊息傳導路徑上。最後，我們發現4個miRNA標記加上HBV基因型的組合，能從HBV帶原者中精確辨認出會進展成為HCC病患的高危險群 (AUC曲線下面積 = 0.88；95% 信賴區間 = 0.80-0.95)。
結論：我們發現多個循環的miRNAs顯著相關於HCC風險，推測可能牽涉HBV感染相關的HCC形成。miRNA指標結合已知的病毒血清標記可能會增加預測HCC風險之能力。

關鍵字

miRNAs ； HCC ； 生物標記 ； 路徑分析 ； AUC

並列摘要

Background and aim: Studies have shown that microRNAs (miRNAs) are involved in carcinogenesis and cellular proliferation through dysregulating cancer-related gene expression. In addition, miRNAs from various tissues can be detected in peripheral blood. Therefore, miRNAs exhibit great potential as biomarkers for application in cancer diagnosis or screening for intervention. The aims of this study were to characterize distinctive circulating miRNA profile in relation to HCC development in hepatitis B virus (HBV) carriers, and to address the possibility that miRNAs might be used as promising novel biomarkers for prediction of HCC risk.
Materials and Methods: A nested case-control study was designed within a published cohort of 2903 HBV carriers who were enrolled between 1989-1992, and followed up through 2009. Cases were matched with randomly selected controls on the timing and age at the time subjects involved in this cohort, and the time of collection of the blood sample. This study was divided into three steps: first, microarray analysis comparing 50 cases and 50 controls by using conditional logistic regression; second, pathway analysis based on miRNAs profiling to provide biological insight; third, use of a signature of significant miRNAs to construct predictive model for HCC risk.
Results: Our microarray analysis revealed 79 miRNAs that significantly differentially expressed in cases compared with controls, among which 7 miRNAs (miR-191-5p, miR-193a-3p, miR-23b-3p, miR-3139, miR-378f, miR-4640-5p, miR-637) have predictive binding sites within the 3’-untranslated regions of a panel of genes involved in ERK/MAPK, insulin receptor, mTOR, PI3K/AKT, or Wnt/β-catenin signaling. Finally, we found 4 miRNA signatures combined with HBV genotype that accurately discriminated HBV carriers at high risk to progress to HCC (area under receiver operation curve = 0.88；95% confidence interval = 0.80-0.95).
Conclusion: We found multiple circulating miRNAs significantly associated with HCC risk, suggesting underlying mechanisms of HBV-related hepatocellular carcinogenesis. A miRNA signature might be used in combination with known viral seromarkers to enhance the accuracy of prediction of HCC risk.

並列關鍵字

miRNAs ； HCC ； biomarker ； pathway analysis ； AUC

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