乳癌之基因微陣列分析研究— 探討基因表現與單核苷酸多型性及微型核醣核酸之關係

Abstract

隨著 cDNA 和 oligonucleotide 微陣列技術的進步，我們可以很快速得取得大量的基因表現數據。這些基因表現數據所建立出來的圖譜可以幫助我們了解癌症機制中基因調控的情形。在本次的研究中，我們分析了59位乳癌病患的基因表現數據並探討雌激素受體陽性和陰性的乳癌病患中，基因表現和單核苷酸多型性( Single nucleotide polymorphisms, 簡稱 SNPs ) 以及微型核醣核酸之間的關係。雌激素受體在乳癌的生長過程中扮演了很重要的角色。第一部分的研究中，我們分析比對了台灣地區59位乳癌病患和英國地區99位乳癌病患的基因表現圖譜。再利用已知的 SNP 資料庫內的資料對這67個基因進行統計分析，找到了17個基因，這17個基因內有一個以上的 SNPs 是在華人和高加索人種間具有顯著差異的。因此我們推斷可能因為這些特定人種內存在的 SNPs ，讓這17個基因的功能直接或是間接影響到不同人種內的雌激素受體調控機制。 微型核醣核酸( microRNAs，簡稱 miRNAs )是一種長度約只有 21-25個核苷酸的核醣核酸。它藉由抑制基因的表現進而影響到許多生物機制。在第二部分的研究中，我們建立出了一套有系統的研究方法，利用基因表現圖譜來加速發現 miRNAs 的功能，並且將 miRNAs 連結到可能參與的生物路徑上。我們發展了一個生物資訊的工具 – miLink 。它整合了 miRNAs ，整合了預測的 miRNAs 標的基因(target genes)資料以及生物路徑的資料庫，同時利用統計分析方法讓使用者可以篩選出可能具有影響的 miRNAs。我們將基因表現的分析結果應用到miLink上，並利用即時定量聚合酶連鎖反應( RT-QPCR )，針對幾組可能和 ER有關的 microRNAs 和標的基因進行定量。藉由分析 miRNAs 和其標的基因表現量之間的關係，我們發現了 miR-218 和其標的基因可能和雌激素受體的表現有關。我們的結果不僅可說明 miLink 在 miRNAs 研究上的實用性，也發現了一些可能和乳癌中雌激素受體調控有關的 miRNAs。

With advanced cDNA and oligonucleotide microarray technique, large amounts of gene expression data can be obtained in a short period of time. Gene expression profiling is a powerful tool for identifying gene activity patterns and discovering pathological mechanisms in cancers. In this study, we analyzed the gene expression data from 59 breast cancer patients in Taiwan and correlated them with SNPs and microRNAs in estrogen receptor (ER)-positive compared to ER-negative breast cancers. Estrogen receptor (ER) activation plays an important role in the progression and development of breast cancer. In the first part, we compared the gene expression profiling in Taiwan with that of 99 breast cancer patients in the United Kingdom to reveal population-unique SNPs in breast cancer of different ethnic origins. Using public SNP databases and statistical analysis, a total of 83 population-unique SNPs in these 17 genes were identified. The association between the distinct expression profiles of these genes in two populations and their population-unique SNPs may imply that these population-unique SNPs are likely related to ER regulation in breast cancer of different populations. MicroRNAs (miRNAs) are mediators of gene expression repression that control many biological processes in development, differentiation, growth and metabolism. In the second part, we built a systematical approach to facilitate the discovery of miRNAs’ functions and link miRNAs to biological pathways by using the gene expression profiling. We developed a web-based bioinformatics tool, miLink, to integrate miRNAs target prediction information and current major biological pathway resources. Moreover, miLink can provide statistical analysis for selection of possible miRNAs that associate with target genes. Applying the analysis results of the gene expression data to miLink, several possible microRNAs and ER-related genes were chosen and quantified by RT-QPCR. Though the comparison of the expression of the miRNAs and target genes, we found that miR-218 and its target genes are associated with different estrogen receptor status. Our results may not only support the practical use of miLink in miRNA functions but also discover the correlation between the miRNAs and genes in ER regulatory mechanisms of breast cancer.