藉由微陣列基因晶片以探討中草藥BP011w對於抑制肺腺癌細胞株爬行及轉移之機制

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吳秉翰(Bing-Han Wu) 查詢紙本館藏

畢業系所

系統生物與生物資訊研究所

論文名稱

藉由微陣列基因晶片以探討中草藥BP011w對於抑制肺腺癌細胞株爬行及轉移之機制
(In vitro analysis of molecular mechanisms underlying effects of Chinese medicine BP011w to inhibit migration of lung adenocarcinoma)

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摘要(中)

肺癌在全世界是最常見且死亡率最高的癌症，在台灣也不例外。許多的病人由於肺腺癌的高轉移性而常常在診斷後被發現已經是癌症晚期。就算病人在診斷後為初期就動手術把腫瘤切除，肺腺癌往往會在數個月後轉移復發並且伴隨著高死亡率，這也是肺癌死亡率居高不下的原因。近年來艾瑞莎(Gefitinib)及得舒緩(Erlotinib)是肺癌最常被使用的標靶藥物，但是兩者都沒有抑制肺腺癌細胞轉移的效果，因此尋找一種全新的藥物來針對抑制肺腺癌的轉移是十分重要的。在我們的研究中，我們想要找到一種中國傳統中藥並且具有抑制肺腺癌細胞爬行及轉移的功能，因為中國傳統中藥相對於化學療法及放射療法有許多的優點，像是低副作用、天然、低毒性、便宜等。在經過細胞學實驗的驗證後，我們發現150 μg/ml濃度的BP011w顯著的抑制CL1-5細胞株的爬行及轉移，經由微陣列基因晶片資料的分析後，我們找到了四個候選基因DYNAP、FGF16、miR-548L及REN。在微陣列基因晶片的資料中，DYNAP、FGF16B及REN在BP011w的藥物處理之後基因為下表現，而MIR-548L則為上表現。DYNAP、FGF16B是和PI3K/AKT路徑相關，FGF16B、REN則是和RAS/ERK路徑相關。最後，我們推測是由於BP011w造成這四個基因表現的變化而導致PI3K/AKT及RAS/ERK的下游訊號被阻擋進而造成抑制肺腺癌細胞株的爬行及轉移。

摘要(英)

Lung cancer is one of the most frequently diagnosed cancers and is the major cause of cancer-related death worldwide, as well as in Taiwan. Most patients were diagnosed with advanced-stage lung adenocarcinomas because of its highly metastatic rate. Even if diagnosed at an early stage and surgically removed, lung adenocarcinomas can recurrence and extending to other organs with a high mortality rate after a few months. Recently, Gefitinib and Erlotinib were the most common target therapy for lung cancer, but both of them can’t inhibit the cell migration. Therefore, it is necessary to find a brand new drug against to the metastatic of lung cancer, especially for lung adenocarcinoma. In our study, we want to search a Traditional Chinese Medicines to inhibit cell migration of lung adenocarcinoma because TCMs have lots of advantages including less side effects, naturally, low toxicity, inexpensive than chemotherapy and radiotherapy. After identify by cytological analysis, we found the dosage of 150 μg/ml BP011w could inhibit CL1-5 migration obviously. After analysis the data of microarray, we found 4 candidate genes, DYNAP, FGF16, MIR-548L and REN. In the microarray data, DYNAP, FGF16 and REN were down-regulated; miR-548L was up-regulated after treating by BP011w. DYNAP and MIR-548L were related to PI3K/AKT pathway, FGF16 and REN were related to RAS/ERK pathway. Finally, we surmised that the change of 4 gene expression could block the downstream signal of PI3K/AKT and RAS/ERK due to the treatment of BP011w.

關鍵字(中)

★ 肺癌
★ CL1-5
★ 非小細胞肺癌
★ 轉移
★ 中草藥
★ 微陣列基因晶片

關鍵字(英)

★ Lung cancer
★ CL1-5
★ Non-small cell lung cancer
★ metastasis
★ Traditional Chinese Medicines
★ microarray

論文目次

Table of contents

中文摘要 i
Abstract ii
Table of contents iii
List of tables v
List of figures vi
List of supplements tables vii
List of supplements figures viii
1. Introduction 1
1-1. Lung cancer 1
1-2. Pathology and clinical stage classification of lung cancer 2
1-3. Metastasis and therapies of lung adenocarcinomas 3
2. Materials and methods 5
2-1. Cell culture 5
2-2. Aqueous extraction of Traditional Chinese Medicines 6
2-3. Wound healing assay 7
2-4. Boyden chamber migration assay 7
2-5. Cell proliferation assay 8
2-6. Flow cytometric analysis for apoptosis and cell cycle 8
2-7. Protein extraction 9
2-8. Western blot assay 10
2-9. RNA extraction 10
2-10. Microarray hybridization 11
2-11. Data analysis 12
3. Results 13
3-1. Experiment workflow 13
3-2. Cytological analysis 13
3-2-1. TCMs screening 13
3-2-2. Cell proliferation in different drug concentrations 15
3-2-3. Cell morphology and apoptosis analysis 16
3-2-4. Cell cycle analysis by flow cytometry 18
3-2-5. Migration analysis by wound-healing assay 20
3-2-6. Migration analysis by Boyden chamber assay 22
3-2-7. Expression of migration-related proteins by western blot 23
3-3. Bioinformatics analysis 26
3-3-1. Genome-wide expression profiling 26
3-3-2. Differential gene expression analysis 27
3-3-3. Function, pathway and protein-protein interaction 28
3-3-4. Candidate genes which were regulated by BP011w 31
3-3-5. Candidate genes which might inhibit cell migration 36
4. Summary and discussion 39
5. Reference 41
6. Supplements 45

List of tables
Table 1. The percentage of total cells for each phase of the cell cycle (G1, S and G2/M) 20
Table 2. The biological process enriched by 1,106 genes 29
Table 3. The cellular component enriched by 1,106 genes 29
Table 4. The KEGG pathway enriched by 1,106 genes 29
Table 5. The 36 up-regulated candidate genes which might inhibit cell migration 32
Table 6. The 67 down-regulated candidate genes which might inhibit cell migration 33

List of figures
Figure 1. Flow diagram of the aqueous extraction 6
Figure 2. Screening of 10 potential TCMs for inhibitory capability on CL1-5 cells by wound healing assay 14
Figure 3. Effect of crude BP011w extracts on the cell proliferation. 15
Figure 4. Effect of crude BP011w extracts on the cell morphology and cell apoptosis 16
Figure 5. Cell cycle percentage of crude BP011w extracts by the cell cytometry 19
Figure 6. BP011w inhibited migration of CL1-5 cells according to the would healing assay . 21
Figure 7. BP011w inhibited migration of CL1-5 cells in the Boyden chamber assay 22
Figure 8. Western blot analysis of CL1-5 treated with different concentrations of BP011w for different time conditions 24
Figure 9. The protein-protein interaction of selected 1,106 genes 30
Figure 10. The flow chat of selecting migration-related genes 31
Figure 11. The heat map of selected 103 genes 35
Figure 12. The gene expression patterns of 4 candidate genes 38

List of supplements tables
Table S1. Stage grouping for non-small-cell lung cancer 45
Table S2. Antibodies for western blot assay 46
Table S3. Experiment buffer reagents for cytological analysis and biochemistry laboratory 47
Table S4. RNA QA / QC information 48

List of supplements figures
Figure S1. The cause of cancer-related death in 2014 and 2004 49
Figure S2. Lung cancer classification 50
Figure S3. The four population of apoptosis analysis by using flow cytometry 51
Figure S4. RNA quality information for array analysis 52
Figure S5. The cell cycle phase in 12 samples 53
Figure S6. The gene expression pattern in dose- and time dependent manner of 36 up-regulated candidate genes 55
Figure S7. The gene expression pattern in dose- and time dependent manner of 67 down-regulated candidate genes 58
Figure S8. The image of GFP- CL1-5 cell 64

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指導教授

蘇立仁

審核日期

2016-7-25

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