The most clinically significant part in tumor biology of choriocarcinoma is its uniquely good response to chemotherapy, particularly in comparison with the intractable human epithelial ovarian cancer. Although high throughput technology is popular for measuring the gene expression of changing genetic conditions and large amount of molecular networks are also public in biological database, the pathology of response to chemotherapy of cancer is still unclear. Microarray data and protein networks allow us to find interactions within the causal relationships to multiple affected genes under drug treatment. However, in search of the large availability of protein-protein interaction data to identify the biological meaningful pathways is regarded as an NP-problem. We proposed a constraint-based pathway inference method to extract the most likely pathways and also satisfy activation/inhibition relationships between protein pairs in the pathways corresponding to the microarray data to explain the drug cause-effect. In the experiments, we tested our methods by applying small networks and large human networks. According to the significant assembled pathway we discovered, the results denoted that methotrexate can block at the G1/S phase transition of the cell cycle while paclitaxel arrest G2/M phase. We observed the different gene expression of P27 may the key protein between choriocarcinoma and ovarian cancer after treated with chemotherapeutic agents, such as methotrexate and paclitaxel. Our predicted results can be found and validate with recent biological knowledge and the merit of this research would help biologists to understand the cellular mechanism s with or without drug effects more easily.

臨床表現在癌症生物學中扮演很重要的角色，雖然透過生物晶片的分析可以了解基因表現的不同，但在同樣的藥物下對癌症的藥物反應仍不清楚。藉著人類基因草圖的完成，從此，基因組研究的知識成果將能為醫學研究帶來更近ㄧ步的知識。我們希望藉由檢視這龐大的人類基因組資料，試著去探討為什麼某些癌症要比別的癌症容易治癒？ 與較難治療的卵巢癌比較時，絨毛膜細胞癌最值得我們深思的腫瘤生物學，就是它對於治療的良好反應。雖然目前已經有大量的技術在探討細胞在不同環境下的基因表現，並且有大量的分子網絡記載於生物資料庫中，但是對於癌症用藥之後的反應途徑仍然無法有很清楚得了解。我們利用DNA微陣列分析技術與蛋白質網路來推論出藥物治療之後對細胞的影響，但是若欲在如此龐大的網路中搜尋出全部有意義的路徑是一個NP問題，所以我們企圖用條件限制的路徑推理來分析絨毛膜細胞癌與卵巢癌在用藥之後不同的基因表現。我們利用小型的有向圖和人類基因網路作為我們的測試資料，依據我們的方法可以發現在用藥之後都會影響細胞週期與細胞凋亡相關的途徑。在實驗結果中發現Methotrexate主要是將細胞阻斷在G1/S階段而Paclitaxel則是將細胞阻斷在G2/M階段，並且發現P27是兩種癌症在用藥後呈現不同反應的關鍵點。希望我們可以藉由我們的研究成果推薦生物學家參與P27反應的路徑及參與的基因，進而找到有效的調控方式而達到治癒的效果。

[1] Greene, M. H., et al. (1984) The epidemiology of. ovarian cancer. Sem Oncol. 11: 209-26
[2] Heintz AP, et al. (1985) Epidemiology and etiology of ovarian cancer: a review. Obstet. Gynecol. Jul. 66(1):127–135.
[3] Yancik R, et al. (1986) Ovarian cancer in the elderly: an analysis of surveillance, epidemiology and end results. Am J Obstet Gynecol 154 (3), 639-47.
[4] Rowinsky, E. K., et al. (1990) Taxol: a novel investigational antimicrotubule agent. J Natl Cancer Inst 82 (15), 1247-59.
[5] Martin Steffen, et al. (2002) Automated modeling of signal transduction networks. BMC Bioinformatics, 3:34.
[6] Jacob Scott, et al. (2005) Efficient algorithms for detecting signaling pathways in protein interaction networks. Ninth Annual International Conference on Research in Computational Molecular Biology, LNBI 3500, 1-13.
[7] M. Ashburner, et al. (2000) Gene Ontology: Tool for the unification of biology. The Gene Ontology Consortium. Nature Genetics, 25(1):25–29.
[8] Falk Huffner, et al. (2008) Algorithm engineering for color-coding to facilitate signaling pathway detection. Algorithmica, 52(2):114–132
[9] Yeang, C.H., et al. (2005) Validation and refinement of gene regulatory pathways on a network of physical interactions. Genome Biology 6(7)
[10] Yeang, C.H., et al. (2006) Physical network models. J.Comput. Biol., 11, 243-262.
[11] Ourfali O, et al. (2007) SPINE: a framework for signaling-regulatory pathway inference from cause-effect experiments. Bioinformatics. 23(13):i359-i366.
[12] Hsueh-Chuan Liu, et al. (2009) BioIR: An approach to public domain resource integration of human protein-protein interaction. The proceeding of the Asia Pacific Bioinformatics Conference (APBC)
[13] Goldberg, D., et al. (2003) Assessing experimentally derived interactions in a small world. Proc. Natl. Acad. Sci. USA 100, 4372-6.
[14]O. Babur, et al. (2004) Pathway Activity Inference Using Microarray Data, bioinformatics, Vol. 1 no. 1
[15] S. Grossmann, et al. (2006). An improved statistic for detecting over-represented gene ontology annotations in gene sets. In 10th International Conference on Research in Computational Molecular Biology (RECOMB’06), 85–98, 2006.
[16] Wishart DS, et al. (2006) DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res. Jan 1;34 (Database issue):D668-72
[17] Chen X, et al. (2002) TTD: Therapeutic Target Database. Nucleic Acids Res. Jan 1;30(1):412-5
[18] Wang TH, et al. (2000) Paclitaxel-induced cell death – where the cell cycle and apoptosis come together. Cancer 88: 2619-28.
[19] Maria Rosa Bani, et al. (2004) Gene expression correlating with response to Paclitaxel in ovarian carcinoma xenografts. Mol. Cancer Ther. 3:111-121.
[20] Reed, J. C. (1995) Regulation of apoptosis by bcl-2 family proteins and its role in cancer and chemoresistance, Curr Opin Oncol. 7: 541-6.
[21] Webb, A., et al. (1997) BCL-2 antisense therapy in patients with non-Hodgkin Lymphoma. Lancet Apr. 19; 349(9059):1137–1141
[22] Cohen, G. M. (1997) Caspases: the executioners of Apoptosis. Biochem J. Aug 15;326 ( Pt 1):1-16
[23] Zhou, B. B., et al. (1998) Caspase-dependent activation of cyclin-dependent kinases during Fas-induced apoptosis in Jurkat cells. Proc Natl Acad Sci USA 95 (12), 6785-90.
[24]Santos AM, et al. (2006) TP53 and P21 polymorphisms: response to cisplatinum/paclitaxel-based chemotherapy in ovarian cancer. Biochem Biophys Res Commun. Feb 3;340(1):256-62. Epub 2005 Dec 9. [25]Rebhan, M, et al. (1997) GeneCards: integrating information about genes, proteins and diseases. Trends in Genetics 13: 163
[26]Judson PL, et al. (1999) Cisplatin inhibits paclitaxel-induced apoptosis in cisplatin-resistant ovarian cancer cell lines: possible explanation for failure of combination therapy. May 15;59(10):2425-32
[27]Fujiwaki R, et al. (2002) Thymidine kinase in epithelial ovarian cancer: relationship with the other pyrimidine pathway enzymes. Int J Cancer. May 20;99(3):328-35