研究生: |
林芷彤 Lin, Chih-Tung |
---|---|
論文名稱: |
Ⅰ、SCNN1B於大腸直腸癌類癌幹細胞之角色探討 / Ⅱ、建立藥物吸收之活細胞即時影像觀測系統 Ⅰ、The role of SCNN1B in stemloid of colorectal cancer / Ⅱ、Establishment of Cellular Live-Imaging Model for drug Absorption |
指導教授: |
賴韻如
Lai, Yun-Ju |
學位類別: |
碩士 Master |
系所名稱: |
生命科學系 Department of Life Science |
論文出版年: | 2018 |
畢業學年度: | 106 |
語文別: | 中文 |
論文頁數: | 70 |
中文關鍵詞: | 大腸直腸癌 、癌幹細胞 、類癌幹細胞 、標靶治療 、SCNN1B 、口服給藥 、藥物吸收 、Caco-2 、薑黃素 |
英文關鍵詞: | Colorectal cancer (CRC), cancer stem cells (CSCs), cancer stemloids, target therapy, SCNN1B, Oral administration, Drug absorption, Caco-2, Curcumin |
DOI URL: | http://doi.org/10.6345/THE.NTNU.SLS.018.2018.D01 |
論文種類: | 學術論文 |
相關次數: | 點閱:165 下載:6 |
分享至: |
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
Ⅰ、大腸直腸癌類癌幹細胞因子之探討
大腸癌 (colorectal cancer, CRC) 又稱為大腸直腸癌或結腸直腸癌,由於其預後效果並不理想,即便經過治療,仍常發生轉移及復發的情形。「癌幹細胞 (cancer stem cells, CSCs)」為腫瘤細胞中極少部分類似幹細胞特性的細胞。然而這些細胞與腫瘤的發生、轉移、抗藥性以及復發擁有密切的關係。目前常用於辨識癌幹細胞的生物標記,如:CD133、CD44等,但這些生物標記仍備受爭議。本研究中我們利用腫瘤病人的新鮮檢體培養得來之貼盤細胞與懸浮細胞球(tumorsphere) 進行微陣列分析 (microarray assay),實驗結果發現SCNN1B基因的表現量在類癌幹細胞中有較一般癌細胞多的趨勢;且在大腸癌細胞株的繼代培養中亦觀察到相同的現象。因此,我們期望透過研究SCNN1B對大腸癌幹細胞 (colorectal cancer stem cells, CRCSCs) 的影響,藉以找出大腸癌治療標靶的新穎生物標記。
Ⅱ、建立藥物吸收之活細胞即時影像觀測系統
一直以來,在臨床上給予藥物最常用的方式是口服給藥,因為口服給藥是最為經濟且安全的,並被認為是病患對於藥物吸收最理想的方式,口服給藥的方式藥物會通過腸道吸收以及血管運送進入人體循環,上皮細胞對於藥物的吸收程度以及藥物對於內皮細胞的穿透能力,被認為是對於藥效影響的指標。目前在臨床研究上有許多方法可以用來偵測藥物在體內以及體外的吸收程度,但這些方法大部分是建立在間接的化學分析或者物理波長的吸光度測定上,因此本研究透過建立一個活細胞即時影像系統,觀察藥物吸收以及藥物進入細胞的過程。利用計算藥物螢光的強度,我們可以偵測藥物或生物活性配方的吸收效率,而我們也成功的在加藥半小時內觀察到薑黃素在Caco-2細胞的吸收情形。此外,我們也觀察到經過高速均質後的薑黃素乳化劑吸收的效率比單純脂質包裹的薑黃素來得高。
Ⅰ、The role of SCNN1B in stemloid of colorectal cancer
Colorectal cancer (CRC), also known as colon cancer, is the third most common cancer in Taiwan. Its prognosis is poor because of high rates of recurrence and metastasis. Cancer stem cells (CSCs) are few percentages of cells in a tumor which have characteristic of stem cell. These cells are related to tumor initiation, metastasis, drug resistance, and relapse. Some biomarkers of CSCs have been found, such as CD133 and CD44. However, these biomarkers are still controversial. To identify more representative genes in regulation of colorectal cancer stem cells (CRCSCs), we performed microarray analysis and identify SCNN1B that expresses higher in tumor spheres than in adherent cancer cells derived from patients’ fresh specimens . We also observed the same phenomenon in CRC cell lines, HCT116 and DLD-1, and the tumorspheres derived from these cells for three passages. By studying the effects of SCNN1B on CRCSCs, we may identify a biomarker that serves as a new target in cancer therapy.
Ⅱ、Establishment of Cellular Live-Imaging Model for drug Absorption
Oral administration is the most common method in taking clinical medicine. It is also the safest, most convenient, and economical way. By oral administration, drug is absorbed by digestive system and enter circulatory system. In the study of drug absorption, it is important to evaluate the relationship of these oral drug formulations and the efficiency of absorption. The level of drug absorption in the epithelial cells and the ability of penetration through the endothelial cell are two important factors that determine the final effects of a drug. Until now, there are many methods to evaluate the drug absorption levels in vitro and in vivo. However, majority of these assays were established on indirect chemical analysis assays or physical wavelength absorbance assay. Therefore, we established a cellular live-imaging model to observe the process of drug absorption and penetration in live cells using real-time microscopy. By measuring the intensity of bio-fluorescence of the drug or a labeled micelle, we can determine the efficiency of the cellular absorption of a specific drug or a formula. Here we successfully observed the curcumin absorption by colon cancer cells Caco-2 in half hour after treatment. Furthermore, the curcumin with high-speed homogenized-emulsion showed the better cellular absorption compared to the lipid-wrapped one.
1. Shangkuan, W.C., et al., Risk analysis of colorectal cancer incidence by gene expression analysis. PeerJ, 2017. 5: p. e3003.
2. O'Connell, J.B., et al., Rates of colon and rectal cancers are increasing in young adults. The American surgeon, 2003. 69(10): p. 866.
3. Siegel, R.L., A. Jemal, and E.M. Ward, Increase in incidence of colorectal cancer among young men and women in the United States. Cancer Epidemiol Biomarkers Prev, 2009. 18(6): p. 1695-8.
4. Santarelli, R.L., F. Pierre, and D.E. Corpet, Processed meat and colorectal cancer: a review of epidemiologic and experimental evidence. Nutrition and cancer, 2008. 60(2): p. 131-144.
5. Ferguson, L.R., Meat and cancer. Meat science, 2010. 84(2): p. 308-313.
6. Hord, N.G., Y. Tang, and N.S. Bryan, Food sources of nitrates and nitrites: the physiologic context for potential health benefits–. The American journal of clinical nutrition, 2009. 90(1): p. 1-10.
7. Kanwar, S.S., A. Poolla, and A.P. Majumdar, Regulation of colon cancer recurrence and development of therapeutic strategies. World J Gastrointest Pathophysiol, 2012. 3(1): p. 1-9.
8. Wolin, K.Y., et al., Physical activity and colon cancer prevention: a meta-analysis. Br J Cancer, 2009. 100(4): p. 611-6.
9. Phua, L.C., et al., Non-invasive fecal metabonomic detection of colorectal cancer. Cancer Biol Ther, 2014. 15(4): p. 389-97.
10. Lin, B.R., et al., Overall Survival of Stage III Colon Cancer with Only One Lymph Node Metastasis Is Independently Predicted by Preoperative Carcinoembryonic Antigen Level and Lymph Node Sampling Status. PLoS One, 2015. 10(9): p. e0137053.
11. Kekelidze, M., et al., Colorectal cancer: current imaging methods and future perspectives for the diagnosis, staging and therapeutic response evaluation. World journal of gastroenterology: WJG, 2013. 19(46): p. 8502.
12. De Rosa, M., et al., Genetics, diagnosis and management of colorectal cancer. Oncology reports, 2015. 34(3): p. 1087-1096.
13. Yeh, Y.-S., et al., Prognostic and molecular factors in stage II colorectal cancer. Genomic Medicine, Biomarkers, and Health Sciences, 2011. 3(1): p. 2-8.
14. Stoehlmacher, J., et al., A multivariate analysis of genomic polymorphisms: prediction of clinical outcome to 5-FU/oxaliplatin combination chemotherapy in refractory colorectal cancer. British journal of cancer, 2004. 91(2): p. 344.
15. Hurwitz, H., et al., Bevacizumab plus irinotecan, fluorouracil, and leucovorin for metastatic colorectal cancer. New England journal of medicine, 2004. 350(23): p. 2335-2342.
16. Koopman, M., et al., Sequential versus combination chemotherapy with capecitabine, irinotecan, and oxaliplatin in advanced colorectal cancer (CAIRO): a phase III randomised controlled trial. The Lancet, 2007. 370(9582): p. 135-142.
17. Chai, J., et al., MicroRNA-494 sensitizes colon cancer cells to fluorouracil through regulation of DPYD. IUBMB Life, 2015. 67(3): p. 191-201.
18. Ma, J., et al., Association between mismatch repair gene and irinotecan-based chemotherapy in metastatic colon cancer. Tumour Biol, 2015. 36(12): p. 9599-609.
19. Gou, H.F., et al., Chemo-immunotherapy with oxaliplatin and interleukin-7 inhibits colon cancer metastasis in mice. PLoS One, 2014. 9(1): p. e85789.
20. Reya, T., et al., Stem cells, cancer, and cancer stem cells. nature, 2001. 414(6859): p. 105.
21. Dawood, S., L. Austin, and M. Cristofanilli, Cancer Stem Cells: Implications for Cancer Therapy: Page 2 of 3. Oncology, 2014. 28(12).
22. O’Brien, C.A., et al., A human colon cancer cell capable of initiating tumour growth in immunodeficient mice. Nature, 2007. 445(7123): p. 106.
23. Ricci-Vitiani, L., et al., Identification and expansion of human colon-cancer-initiating cells. Nature, 2007. 445(7123): p. 111.
24. Shmelkov, S.V., CD133 expression is not restricted to stem cells, and both CD133(+) and CD133(–) metastatic colon cancer cells initiate tumors. 2008. 118(6): p. 2111-20.
25. Nagata, H., et al., CD133 expression predicts post-operative recurrence in patients with colon cancer with peritoneal metastasis. International journal of oncology, 2018. 52(3): p. 721-732.
26. Mérillat, A.-M., et al., Conditional gene targeting of the ENaC subunit genes Scnn1b and Scnn1g. American Journal of Physiology-Renal Physiology, 2009. 296(2): p. F249-F256.
27. <Importance of ENaC-Mediated Sodium Transport in Alveolar Fluid Clearance Using Genetically-Engineered Mice.pdf>.
28. Qian, Y., et al., Sodium channel subunit SCNN1B suppresses gastric cancer growth and metastasis via GRP78 degradation. Cancer research, 2017: p. canres. 1595.2016.
29. Anaya, J., OncoLnc: linking TCGA survival data to mRNAs, miRNAs, and lncRNAs. PeerJ Computer Science, 2016. 2: p. e67.
30. Chandrashekar, D.S., et al., UALCAN: a portal for facilitating tumor subgroup gene expression and survival analyses. Neoplasia, 2017. 19(8): p. 649-658.
31. Tomczak, K., P. Czerwińska, and M. Wiznerowicz, The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge. Contemporary oncology, 2015. 19(1A): p. A68.
32. Khoury, J.D., et al., The landscape of DNA virus associations across human malignant cancers using RNA-Seq: an analysis of 3775 cases. Journal of virology, 2013: p. JVI. 00340-13.
33. Fiske, J.L., et al., Voltage-sensitive ion channels and cancer. Cancer Metastasis Rev, 2006. 25(3): p. 493-500.
34. Le Guennec, J.Y., et al., Voltage-gated ion channels, new targets in anti-cancer research. Recent Pat Anticancer Drug Discov, 2007. 2(3): p. 189-202.
35. Pardo, L.A., et al., Role of voltage-gated potassium channels in cancer. J Membr Biol, 2005. 205(3): p. 115-24.
36. Kunzelmann, K., Ion channels and cancer. J Membr Biol, 2005. 205(3): p. 159-73.
37. Berdiev, B.K., et al., Acid-sensing ion channels in malignant gliomas. J Biol Chem, 2003. 278(17): p. 15023-34.
38. Abdul, M. and N. Hoosein, Voltage-gated sodium ion channels in prostate cancer: expression and activity. Anticancer Res, 2002. 22(3): p. 1727-30.
39. Wiegering, A., et al., Reactivating p53 and Inducing Tumor Apoptosis (RITA) Enhances the Response of RITA-Sensitive Colorectal Cancer Cells to Chemotherapeutic Agents 5-Fluorouracil and Oxaliplatin. Neoplasia, 2017. 19(4): p. 301-9.
40. Lane, D.P., Cancer. p53, guardian of the genome. Nature, 1992. 358(6381): p. 15-6.
41. Glamočlija, U. and A. Jevrić-Čaušević, Genetic polymorphisms in diabetes: Influence on therapy with oral antidiabetics. Acta Pharmaceutica, 2010. 60(4): p. 387-406.
42. Turner, J.R., Intestinal mucosal barrier function in health and disease. Nature Reviews Immunology, 2009. 9(11): p. 799.
43. Balimane, P.V., S. Chong, and R.A. Morrison, Current methodologies used for evaluation of intestinal permeability and absorption. Journal of pharmacological and toxicological methods, 2000. 44(1): p. 301-312.
44. Shafiroff, B., Q.Y. Kau, and H. Baron, The Anatomy of Kerckring's Valves: Case Report on Their Maldevelopment. Annals of surgery, 1959. 149(4): p. 486.
45. Hidalgo, I.J., Assessing the absorption of new pharmaceuticals. Current topics in medicinal chemistry, 2001. 1(5): p. 385-401.
46. Gibaldi, M., R. Boyes, and S. Feldman, Influence of first‐pass effect on availability of drugs on oral administration. Journal of pharmaceutical sciences, 1971. 60(9): p. 1338-1340.
47. Chen, X., et al., A novel design of artificial membrane for improving the PAMPA model. Pharmaceutical research, 2008. 25(7): p. 1511-1520.
48. Hillgren, K.M., A. Kato, and R.T. Borchardt, In vitro systems for studying intestinal drug absorption. Medicinal research reviews, 1995. 15(2): p. 83-109.
49. Lipinski, C.A., et al., Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced drug delivery reviews, 1997. 23(1-3): p. 3-25.
50. Van Breemen, R.B. and Y. Li, Caco-2 cell permeability assays to measure drug absorption. Expert opinion on drug metabolism & toxicology, 2005. 1(2): p. 175-185.
51. Kansy, M., F. Senner, and K. Gubernator, Physicochemical high throughput screening: parallel artificial membrane permeation assay in the description of passive absorption processes. Journal of medicinal chemistry, 1998. 41(7): p. 1007-1010.
52. Stintzing, F.C. and R. Carle, Functional properties of anthocyanins and betalains in plants, food, and in human nutrition. Trends in Food Science & Technology, 2004. 15(1): p. 19-38.
53. Egan, W.J. and G. Lauri, Prediction of intestinal permeability. Advanced drug delivery reviews, 2002. 54(3): p. 273-289.
54. Doluisio, J.T., et al., Drug absorption I: An in situ rat gut technique yielding realistic absorption rates. Journal of pharmaceutical sciences, 1969. 58(10): p. 1196-1200.
55. Wilson, T.H. and G. Wiseman, The use of sacs of everted small intestine for the study of the transference of substances from the mucosal to the serosal surface. The Journal of physiology, 1954. 123(1): p. 116-125.
56. Kerns, E.H. and L. Di, Pharmaceutical profiling in drug discovery. Drug discovery today, 2003. 8(7): p. 316-323.
57. Ussing, H.H. and K. Zerahn, Active transport of sodium as the source of electric current in the short‐circuited isolated frog skin. Acta physiologica Scandinavica, 1951. 23(2‐3): p. 110-127.
58. Balimane, P.V. and S. Chong, Cell culture-based models for intestinal permeability: a critique. Drug discovery today, 2005. 10(5): p. 335-343.
59. Artursson, P., K. Palm, and K. Luthman, Caco-2 monolayers in experimental and theoretical predictions of drug transport1. Advanced drug delivery reviews, 2001. 46(1-3): p. 27-43.
60. Hilgers, A.R., R.A. Conradi, and P.S. Burton, Caco-2 cell monolayers as a model for drug transport across the intestinal mucosa. Pharmaceutical research, 1990. 7(9): p. 902-910.
61. Mainprize, T. and L. Grady. Standardization of an in vitro method of drug absorption. in Pharmacopeial Forum. 1998. USPC UNITED STATES PHARMACOPEIAL CONVENTION.
62. Artursson, P., Epithelial transport of drugs in cell culture. I: A model for studying the passive diffusion of drugs over intestinal absorbtive (Caco‐2) cells. Journal of pharmaceutical sciences, 1990. 79(6): p. 476-482.
63. Hidalgo, I.J., T.J. Raub, and R.T. Borchardt, Characterization of the human colon carcinoma cell line (Caco-2) as a model system for intestinal epithelial permeability. Gastroenterology, 1989. 96(3): p. 736-749.
64. Alves, M., et al., Taxifolin: evaluation through ex vivo permeations on human skin and porcine vaginal mucosa. Current drug delivery, 2018.