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標題: | 漢民族乳癌基因表現與競爭基因雜交之同向變異分析 Concurrent Analysis of Gene Expression and Comparative Genomic Hybridization for Han Chinese Breast Cancer |
作者: | Chi-Cheng Huang 黃其晟 |
指導教授: | 莊曜宇 |
關鍵字: | 乳癌,競爭性基因雜交,同向性基因,基因表現,漢民族,基因微陣列, breast cancer,comparative genomic hybridization,concurrent genes,gene expression,Han Chinese,microarray, |
出版年 : | 2014 |
學位: | 博士 |
摘要: | 基因拷貝數目變異(copy number variation, CNV)和差異性基因表現間的相互關聯可以增進乳癌分子醫學的了解並找出癌症相關的標的基因。在本研究中,我們使用微陣列基因晶片找出在競爭性基因雜交(comparative genomic hybridization, CGH)和基因表現間有同向性變異的基因,並使用這些同向性基因來建立漢民族乳癌的基因標記。
我們對台灣乳癌檢體進行了23片競爭性基因雜交和81片基因表現的微陣列基因晶片,其中有21組檢體同時進行了競爭性基因雜交和基因表現兩種實驗。我們把在兩種平台上有一致性變異的同向性基因找出,並使用這些同向性基因建立臨床雌激素接受體ER、人類上皮生長因子接受體第二型HER2和無疾病存活期相關的基因標記。 同向性基因標記基因的分布和染色體的位置有強烈的關聯:如雌激素接受體ER 標記基因多位於第16號染色體,人類上皮生長因子第二型接受體HER2標記基因位於第17號染色體。我們使用了16個基因(RCAN3, MCOLN2, DENND2D, RWDD3,ZMYM6, CAPZA1, GPR18, WARS2, TRIM45, SCRN1, CSNK1E,HBXIP, CSDE1, MRPL20, IKZF1,與COL20A1)建立的第一主成分來建立乳癌風險預測模型,在合併408 片微陣列晶片組成的漢民族乳癌研究對象中,預測高風險和低風險的乳癌病患表現出不同的存活趨勢。經歷復發、遠端轉移或死亡的病患比起無病存活者有顯著較高的危險分數(0.241 相對於0,P值小於0.001)。在分組分析中,不論臨床雌激素接受體和人類上皮生長因子接受體第二型的狀態,同向性基因標記乳癌風險預測模型都能維持其鑑別能力。與其他已發表的乳癌基因標記相比,乳癌同性性基因標記有較佳的預後鑑別力,其中許多同向性基因標的無法由傳統的表現型相關或基因個別變異的篩選方式辨識篩選出來。 藉由同時進行競爭性基因雜交和基因表現的數據分析,我們可以找出乳癌中具預後價值的生物標記。 The interplay between copy number variation (CNV) and differential gene expression may be able to shed light on molecular process underlying breast cancer and lead to the discovery of cancer-related genes. In the current study, genes concurrently identified in array comparative genomic hybridization (CGH) and gene expression microarrays were used to derive gene signatures for Han Chinese breast cancers. We performed 23 array CGHs and 81 gene expression microarrays in breast cancer samples from Taiwanese women. Genes with coherent patterns of both CNV and differential gene expression were identified from the 21 samples assayed using both platforms. We used these genes to derive signatures associated with clinical ER and HER2 status and disease-free survival. Distributions of signature genes were strongly associated with chromosomal location: chromosome 16 for ER and 17 for HER2. A breast cancer risk predictive model was built based on the first supervised principal component from 16 genes (RCAN3, MCOLN2, DENND2D, RWDD3, ZMYM6, CAPZA1, GPR18, WARS2, TRIM45, SCRN1, CSNK1E, HBXIP, CSDE1, MRPL20, IKZF1, and COL20A1), and distinct survival patterns were observed between the high- and low-risk groups from the combined dataset of 408 microarrays. The risk score was significantly higher in breast cancer patients with recurrence, metastasis, or mortality than in relapse-free individuals (0.241 versus 0, P<0.001). The concurrent gene risk predictive model remained discriminative across distinct clinical ER and HER2 statuses in subgroup analysis. Prognostic comparisons with published gene expression signatures showed a better discerning ability of concurrent genes, many of which were rarely identifiable if expression data were pre-selected by phenotype correlations or variability of individual genes. We conclude that parallel analysis of CGH and microarray data, in conjunction with known gene expression patterns, can be used to identify biomarkers with prognostic values in breast cancer. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/58014 |
全文授權: | 有償授權 |
顯示於系所單位: | 生醫電子與資訊學研究所 |
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