結直腸癌（CRC）是全世界第三大診斷癌症。導致CRC發展和進展的機制是複雜的並且涉及遺傳和表觀遺傳調節。在這項研究中，我們採用系統生物學方法和全基因組高通量數據來研究結直腸癌。通過在結腸直腸癌細胞的每個階段的大型數據庫挖掘和微陣列數據，我們構建了蛋白質 - 蛋白質相互作用網絡（PPIN）和基因調控網絡（GRN），將它們組合在一起作為全基因組遺傳和表觀遺傳網絡（GWGEN）結直腸癌的每個階段。然後我們通過主網絡投影（PNP）方法從GWGENs中提取每個階段結直腸癌的核心GWGEN，並將這些核心GWGEN投射到KEGG途徑進行進一步分析。最後，我們比較了這些相鄰的核心途徑及其靶基因，以研究各階段結直腸癌進展分子機制的致癌生物標誌物。基於每個進展階段的致癌生物標誌物，我們通過藥物數據挖掘選擇了多種藥物設計用於多種藥物設計，以防止CRC的進展。此外，選擇與細胞凋亡和遷移相關的MUC2，HECTD3，SMC2，GDNF和MINK1作為潛在的多藥靶標;多西紫杉醇，洛莫司汀和他莫昔芬被認為是早期至中期CRC相應的多種藥物分子。選擇與細胞增殖和遷移相關的SMC2，STK17B，LRRN1，MINK1和LIG3作為潛在的多藥靶標;從中期到晚期，NOS，卡鉑和紫杉醇被認為是CRC中相應的多種藥物分子。該方法不僅可以研究CRC的進展分子機制，而且可以為CRC的多藥設計提供潛在的多分子靶點。

Colorectal cancer (CRC) is the third most diagnosed cancer all over the world. The mechanisms leading to development and progression of CRC are complicated and implicated in both genetic and epigenetic regulation. In this study, we employ systems biology method and genome-wide high throughput data to investigate colorectal cancer. By big database mining and microarray data in each stage of colorectal cancer cells, we constructed the protein-protein interaction networks (PPINs) and gene-regulatory networks (GRNs) combining them together as genome-wide-genetic and epigenetic networks (GWGENs) for each stage of colorectal cancer. Then we extracted core GWGENs of each stage colorectal cancer from their GWGENs by principal network projection (PNP) method and projected these core GWGENs to KEGG pathways for further analysis. Finally, we compared these neighboring core pathways and their target genes to investigate carcinogenic biomarkers for progression molecular mechanisms of colorectal cancer in each stage. Based on carcinogenic biomarkers in each progression stage, we selected several multiple drug targets for multiple drugs design through drug data mining to prevent the progression of CRC. Moreover, MUC2, HECTD3, SMC2, GDNF, and MINK1 associating with cell apoptosis and migration were selected as potential multiple drug targets; docetaxel, lomustine, and tamoxifen were suggested as the corresponding multiple drug molecules in CRC from early-stage to mid-stage. SMC2, STK17B, LRRN1, MINK1, and LIG3 associating with cell proliferation and migration were selected as potential multiple drug targets; NOS, Carboplatin, and Paclitaxel were suggested as the corresponding multiple drug molecules in CRC from mid-stage to late-stage. The proposed method could not only investigate the progression molecular mechanisms of CRC but also provide potential multiple molecular targets for multiple drug design of CRC.
Keyword: DNA methylation; multiple potential drugs miRNAs; principal network projection; mechanism of CRC progression.

Contents
摘要 i
Abstract ii
Chapter 1 Introduction 1
Chapter 2 Results 5
2.1 The real GWGENs, core GWGENs and their corresponding core pathways in each stage of colorectal cancer cells 5
2.2 The differential core pathways from early-stage to mid-stage colorectal cancer cells 7
2.3 The differential core pathways from mid-stage to late-stage colorectal cancer cells 9
Chapter 3 Discussion 11
3.1 Genetic and epigenetic progression mechanisms from early-stage to mid-stage colorectal cancer via cell apoptosis and migration 11
3.2 Genetic and epigenetic progression mechanisms from mid-stage to late-stage colorectal cancer via cell migration and proliferation 16
3.3 Genetic and epigenetic carcinogenic mechanisms from early-stage to late-stage colorectal cancer cells 17
3.4 Multiple molecule drugs design for each stage of colorectal cancer by drug targets and drug data mining 19
Chapter 4 Conclusion 21
Chapter 5 Materials and Methods 22
5.1 Big data mining to construct candidate GWGEN 22
5.2 Constructing the systematic models for the GWGENs 23
5.3 System identification of candidate GWGEN via genome-wide microarray data 26
5.4 System order detection scheme for pruning the false positives of candidate to obtain the real GWGENs of early-stage colorectal cancer to late-stage colorectal cancer 33
5.5 Principle network extraction of core GWGENs from real GWGENs by applying the PNP method 35

Tables 39
Table 1. The number of edges and nodes in candidate GWGENs and identified GWGENs in each stage of colorectal cancer. 39
Table 2. The pathway enrichment analysis of proteins in the real GWGENs of early-stage colorectal cancer. 40
Table 3. The pathway enrichment analysis of proteins in the real GWGENs of mid-stage colorectal cancer. 41
Table 4. The pathway enrichment analysis of proteins in the real GWGENs of late-stage colorectal cancer. 41
Table 5. The drug targets and the corresponding multiple molecule drugs for early and mid-stage colorectal cancer. 42
Table 6. The drug targets and the corresponding multiple molecule drugs for mid and late-stage colorectal cancer. 44
Table 7. Compare with dukes’ stage, TNM stage, and our stage method 46
Figures 47
Figure 1. The flowchart of applying systems biology approach to construct the genetic and epigenetic networks (GWGENs) for core pathways to investigate the molecular progression mechanisms of colorectal cancer development for investigating genetic and epigenetic biomarkers as multiple drug targets of each stage of colorectal carcinogenesis. 48
Figure 2. Real GWGEN of early-stage progression of colorectal cancer. 49
Figure 3. Real GWGEN of mid-stage progression of colorectal cancer. 49
Figure 4. Real GWGEN of late-stage progression of colorectal cancer. 50
Figure 5. Core GWGEN of early-stage progression of colorectal cancer. 50
Figure 6. Core GWGEN of mid-stage progression of colorectal cancer. 51
Figure 7. Core GWGEN of late-stage progression of colorectal cancer. 51
Figure 8. The differential core pathways for investigating the progression carcinogenic mechanism from early-stage colorectal cancer cells to mid-stage colorectal cancer cells. 52
Figure 9. The differential core pathways for investigating the progression carcinogenic mechanism between mid-stage colorectal cancer cells and late-stage colorectal cancer cells. 53
Figure 10. The overview of progression genetic and epigenetic carcinogenic mechanisms from early cells to late-stage colorectal cancer cells 54
Reference 55

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