利用非線性的隨機模型來建立並比較正常與癌症細胞中蛋白質的交互作用網路

Construction and Comparison of Protein-Protein Interaction Networks between Normal and Cancer Cells via Nonlinear Stochastic Model

陳瑞延(Jui-Yen Chen)

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/碩士(2006年)

https://doi.org/10.6843/NTHU.2006.00284

摘要

癌症的產生是由於前致癌基因(proto-oncogenes)或抑癌基因(tumor suppressor genes)的基因改變，造成一連串下游的蛋白質訊息傳遞發生改辨或是喪失抑制癌症發生的功能。因此檢是癌症細胞內的蛋白質作用，並將其與正常細胞做比較，能夠幫助我們更了解正常細胞是如何轉化為癌症細胞。在這篇研究中，我們以HeLa癌症細胞株(HeLa cancer cell line)的表現曲線(expression profiles)為根據，並利用一個非線性的隨機模型來描述癌症細胞中蛋白質和蛋白質複合物(protein complexes)的動態作用，進一步建立出癌症細胞中的蛋白質交互作用網路。
再來，我們提供一個有系統的方法來建立並比較正常細胞與癌症細胞中的蛋白質交互作用網路。透過我們的方法並選取那些在前致癌基因和抑癌基因中扮演重要角色的蛋白質作為我們的目標蛋白質(target protein)，能夠得到正常細胞與癌症細胞中不同的蛋白質反應。這些不同的蛋白質反應提供了一些癌症產生的線索，同時我們也試著去尋找一些文獻證據來印證利用我們的方法所得到的結果。最後，我們也試著利用我們的方法建立在正常細胞與癌症細胞中MAPK訊息傳遞路徑的蛋白質交互作用網路。我們所提出的方法在比較正常細胞與癌症細胞中蛋白質交互作用上非常有用，而且也可能在未來的癌症藥物設計上提供貢獻。

關鍵字

蛋白質交互作用 ； 隨機模型 ； 正常細胞與癌症細胞的比較

並列摘要

Cancer is known to occur due to the genetic alternations of proto-oncogenes or tumor suppressor genes to alter a series of downstream signal transduction pathway in the molecular level or loss function in inhibiting the tumor occurrence. Therefore, inspecting the interactive behaviors of proteins in cancer cells and comparing them with those in normal cells will help us understand more about how a normal cell transforms to a cancer cell. In this study, we develop a nonlinear stochastic model to interpret the dynamic interactions among proteins and protein complexes in cancer cells based on the expression profiles of the cancer cell lines (HeLa) to depict a protein-protein interaction network of cancer cells. Furthermore, we provide a systematic method for construction and comparison of protein-protein interactions between normal and cancer cells. By choosing the target proteins of the protein-protein interaction network known to play important roles in proto-oncogenes and tumor suppressor genes such as Fos protein, Rb1 protein, Tp53 protein, etc. via our method, differential interactions between normal and cancer cells could be shown. These differences will provide a clue to the formations of tumors, and then we find some literature evidences to validate these results. Finally, protein-protein interaction networks of the MAPK signal transduction pathways between normal and cancer cells are also depicted via the proposed method. The proposed method is useful for enhancement and comparison of protein-protein interactions between normal and cancer cells, and may be helpful in the drug design in the future.

並列關鍵字

protein-protein interactions ； stochastic model ； comparison between normal and cancer cells

參考文獻

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