利用微陣列之差異性基因表現尋找癌症相關基因

Discovering Cancer-related Genes based on Differential Expression of cDNA Microarray

沈詩珊(Shen Shih-Shan)

指導教授 ： 陳榮銘 ； 張建國

亞洲大學/資訊學院/生物資訊學系碩士班/碩士(2004年)

摘要

癌症的形成是多步驟性的，其中包括致癌基因的過度活化、抑癌基因的不活化、DNA修補基因以及其他相關因子的突變，造成細胞生長、分化、繁殖及死亡過程產生改變。而其中又以致癌基因的過度表現在許多癌症發生的起始階段扮演了非常重要的角色。此外，抑癌基因是可抑制致癌症的發生，如果抑癌基因的正常功能喪失，就會增加癌症的發生率。目前有許多抑癌基因已被鑑定出來，但致癌基因則仍只是冰山一角，大部份的致癌基因等待我們去發掘。在人類基因中來尋找導致基因突變的原因是很難的，尤其是使用傳統的分析方法。而目前不同癌細胞中各種基因表現量的變化已可利用微陣列進行同時大量基因的表現分析。過去幾年裡，有關生物上癌症的研究已經累積了相當的微陣列基因表現資料，如何利用這龐大的癌症微陣列資料挖掘出有用的訊息，藉以尋找出可能的癌症相關基因是一件非常有趣與有貢獻的研究。
本篇論文主旨是將藉由分析癌症微陣列基因表現數據，利用基因的差異性表現來篩選出可能的癌症相關基因，並使用統計學上估計檢定的T-test驗證差異性表現結果的可信度，藉以尋找出具有生物實驗研究價值的癌症相關基因，並協助生物學家定義癌症相關基因表現值的範圍。

關鍵字

生物資訊 ； 致癌基因 ； 抑癌基因 ； 微陣列基因表現 ； T檢定

並列摘要

The processes of oncogenesis are multiple steps, which include the activation of oncogenes, inactivation of tumor suppressor genes, and the mutations of DNA repair genes and other cancer-related factors. All the above phenomena cause changes in the processes of cell growth, differentiation, reproducing, and apoptosis. Especially, the over-expression of oncogenes plays a very important role in the initial state of numerous cancer cases. On the other hand, tumor suppressor genes are the brakes of growth. Loss of function in tumor suppressor genes makes the tumor formation more possible. Many tumor suppressor genes had been identified in the past. However, oncogenes that have been identified present only the tip of the iceberg. More oncogenes are waiting us to discover. Mining the human genome to identify genetic mutations that cause cancer is like looking for needles in a haystack, especially by using the traditional one-by-one analysis method. For now, cDNA microarray can be used to analyze the changes of the gene expression in different cancer cells in a high throughput manner. A lot of microarray data had been accumulated from the cancer-related researches in the past. It is quite interesting to mine useful information from these data to find possible cancer-related genes.
In this thesis, we propose a bioinformatic approach to discover possible cancer-related genes based on differential expression of cDNA microarray databases for cancer and normal tissues. The t-test is also used to assess the significance of the differential expression. The proposed cancer-related genes discovering system will narrow down the range of bio-experiments and avoid some unnecessary experiments. It can really help the biologist to seek the cancer-related genes more efficient.

並列關鍵字

Bioinformatics ； Oncogene ； Tumor suppressor gene ； Microarray ； T-test

參考文獻

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