利用生物網路標記進行肺癌分子研究及診斷

A network-based biomarker approach for molecular investigation and diagnosis of lung cancer

王禹超(Yu-Chao Wang)

指導教授 ： 陳博現

國立清華大學/電機資訊學院/電機工程學系/博士(2010年)

https://doi.org/10.6843/NTHU.2010.00524

摘要

Lung cancer is the leading cause of cancer deaths worldwide. Many studies have investigated the carcinogenic process and identified the biomarkers for signature classification. However, to the best of knowledge, there is no satisfactory network-based method for carcinogenesis characterization and diagnosis from the system perspective. In this study, a systems biology approach, which integrated microarray gene expression profiles and protein-protein interaction information, was proposed to develop a network-based biomarker for molecular investigation and diagnosis of lung cancer. The network-based biomarker consists of two protein association networks constructed for cancer samples and for non-cancer samples. Based on the network-based biomarker, a total of 40 significant proteins are identified with carcinogenesis relevance values (CRVs) to gain an insight into the network mechanism of lung carcinogenesis. In addition, the network-based biomarker is also acted as the diagnostic tool, demonstrated to be effective to diagnose the smokers with lung cancer. The results show that the network-based biomarker through constructed protein association networks successfully sheds light on the pathways and mechanisms in lung carcinogenic process and, most importantly, provides potential therapeutic targets to combat against cancer.

關鍵字

生物網路標記 ； 系統生物學 ； 蛋白質關聯性網路 ； 分子治療目標 ； 肺癌

並列摘要

癌症是一種細胞不正常的增生而造成腫瘤的一種複雜的疾病，而肺癌又是眾多癌症中致死率最高、全世界造成死亡數最多的一種癌症。有許多的論文致力於研究致癌的過程以及尋找可以分類特徵的生物標記，這樣的癌症生物標記通常被用來當作診斷評估的工具或是預後情況的指標。然而，就我們所知，目前並沒有令人滿意的以網路為基礎的方法，從系統的觀點來研究致癌的機制及診斷。因此，在這篇論文中，我們提出了一個結合微陣列基因表現以及蛋白質交互作用資訊的系統生物學方法，用來發展生物網路標記以進行肺癌分子研究及診斷。我們利用這樣的資料，結合一個簡單的線性迴歸模型以及系統鑑別與統計方法來建構蛋白質關聯性網路，而從癌症樣本以及非癌症樣本所建構出來的兩個蛋白質關聯性網路就組成了生物網路標記。根據這個生物網路標記，配合致癌關聯數值的計算，我們總共找出了四十個重要的蛋白質，並藉此來瞭解形成肺癌的網路機制。此外，這個生物網路標記也可以用來當作肺癌診斷的工具，可以有效的診斷出具有肺癌的吸煙者。以上這些結果顯示出這個包含蛋白質關聯性網路的生物網路標記可以讓我們對於形成肺癌的過程以及機制更加瞭解，更重要的是，我們找出的那些重要的蛋白質提供了可能的分子目標來治療癌症。

並列關鍵字

network-based biomarker ； systems biology ； protein association network ； molecular therapeutic target ； lung cancer

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