在台灣女性乳癌為致死原因中排名第二位好發惡性腫瘤。目前已知特定因子增加罹患乳癌之風險，如：基因突變及放大、放射線、生活習慣、肥胖及酗酒等。雖然目前已開發出一些具有治療乳癌的蛋白質藥物和小分子藥物，然而乳癌在治癒上有一定的困難度與失敗率。因此開發新的乳癌治療目標為基礎醫學的一個重要研究方向。為了探討具有治療潛力的基因，我們期望利用生物資訊來開發具有潛力的目標基因。首先我們藉由 Oncomine 資料庫分析後發現 CCDC167 基因在乳癌組織中有過度表現的情形。進一步使用 PrognoScan、Kaplan Meier plotter、STRING及The human protein ATLAS 資料庫分析乳腺癌組織中CCDC167的角色和病人存活率。結果顯示乳腺癌患者樣本中CCDC167基因表達增加而導致乳癌患者存活率顯著降低。另一方面，此外透過Real-time PCR 分析M10，MCF-7，MDA- MB-468和MDA-MB- 231 細胞中CCDC167的表現。結果得知MCF-7，MDA- MB-468和MDA-MB- 231 細胞中CCDC167 mRNA有較高的表現情形。我們進一步觀察MCF-7 shCCDC167細胞在細胞生長和集落形成能力的影響，結果顯MCF-7 CCDC167 shRNA 的細胞增生能力及集落形成能力明顯受到抑制。未來我們將評估CCDC167在乳癌發展的作用。本研究的結果可以作為開發乳癌新型治療靶基因的基礎。

Breast cancer is the second leading cause of death in women with malignant tumors in Taiwan. It is known that some factors involed the risk of breast cancer, such as gene mutation and amplification, radiation, lifestyle, obesity and alcoholism. Though some protein drugs and small molecule drugs have been developed for the treatment of breast cancer, but breast cancer in the cure have a certain degree of difficulty and failure rate. Therefore, the development of new therapeutic targets for breast cancer is an important research direction of basic medicine. In order to explore genes with therapeutic potential, we expect to use biological information to develop potential target genes. First, the result show that overexpression of CCDC167 gene was observed in breast cancer from Oncomine database. Furthermore, expression level of CCDC167 in breast cancer tissues and survival rate for breast cancer patients were analyzed by using Survnexpress, PROGene, PrognoScan, Kaplan Meier plotter, STRING The human protein ATLAS and database. The result indicated that CCDC167 gene expression increased in the samples of breast cancer patients, and leading to significant reduction in the survival rate of the patients. Furthermore, the expression of CCDC167 in M10, MCF-7, MDA-MB-468 and MDA-MB-231 cells were determined by Real-time PCR. The results showed that the overexpression of CCDC167 mRNA in MCF-7, MDA-MB- 468 and MDA-MB- 231 cells. In addition, reduction of cell growth and colony formation ability was observed in MCF-7 shCCDC167 cells. In the future, we will evaluate the role of CCDC167 in breast cancer development. The outcome of the current study may server as a basis to develop a novel therapeutic target gene for breast cancer.

目錄
中文摘要 I
Abstract III
致謝 IV
目錄 VI
英文縮寫對照表 XII
第一章 緒論 1
1.1 乳癌 1
1.1.1 乳癌成因 2
1.1.2 乳癌指標 3
1.1.3 乳癌治療 4
1.2 生物資訊 5
1.2.1 Oncomine 6
1.2.2 PrognoScan 6
1.2.3 Kaplan Meier plotter 6
1.2.4 STRING 7
1.2.5 The human protein ATLAS 7
1.3 CCDC176 基因 7
1.4 研究動機 8
第二章 材料與方法 9
2.1生物資訊網站 9
2.1.1 Oncomine數據庫分析 9
2.1.2 Prognoscan數據庫分析 9
2.1.3 Kaplan-Meier plotter 數據庫分析 9
2.1.4 STRING 數據庫分析 10
2.1.5 The human protein ATLAS數據庫分析 10
2.2材料 10
2.2.1藥品 10
2.2.2 試劑 11
2.2.3 儀器 12
2.3 細胞培養 12
2.3.1 細胞株 12
2.3.2 細胞培養條件 13
2.3.3 細胞繼代培養 14
2.3.4 計數細胞 15
2.3.5 冷凍細胞 15
2.3.6 解凍細胞 15
2.4 細菌之培養條件 16
2.5 質體 DNA的純化 16
2.6 DNA 濃度及純度測定 17
2.7 即時聚合酶鏈鎖反應 (Real-time PCR) 18
2.7.1 抽取細胞培養 total RNA 18
2.7.2 反轉錄聚合酶連鎖反應 19
2.7.3 Real-time polymerase chain reaction 19
2.8 細胞轉染 20
2.9 病毒轉染 21
2.10 Colony Formation 22
2.11 細胞存活率分析 ( MTT assay) 22
第三章 結果 24
3.1 乳癌與基因的關係 24
3.2 CCDC167 基因在乳癌細胞中表現量 25
3.3 分析 shCCDC167在MCF-7細胞株的表現 26
第四章 討論 27
第五章 結論 29
第六章 參考文獻 30
附錄 48













圖目錄
圖 1. Oncomine資料庫分析乳癌相關基因 32
圖 2.CCDC167 mRNA在多種癌症中表現量 33
圖 3.CCDC167基因在腦癌(A)(B)中基因相對表現量 34
圖 4.CCDC167基因在乳癌(C)及結腸直腸癌(D)中基因相對表現量 35
圖 5.CCDC167基因在肺癌(F)中基因相對表現量 36
圖 6.CCDC167基因在各種癌症中相對表現量 36
圖 7.CCDC167基因在多種癌症中的風險比 37
圖 8. PrognoScan資料庫分析CCDC167基因在於肺癌中具有高表現 ..38
圖 9. PrognoScan 資料庫分析CCDC167基因在於乳癌中具有高表現. 39
圖 10.Kaplan Meier plotter資料庫分析CCDC167基因在乳癌中具高表現及低存活率 40
圖 11.以STRING尋找和CCDC167具關連性之基因 41
圖 12.CCDC167基因在不同癌症中皆有RNA表達 42
圖 13.以免疫組織化學腫瘤組織切片評估CCDC167基因表達 43
圖 14.以Real-time PCR分析三株乳癌細胞中CCDC167基因表現量 44
圖 15. 以Real-time PCR分析三株 shCCDC167 在 MCF-7 細胞中CCDC167基因表現量 45
圖 16. 以 Colony Formation 分析MCF-7 與三株shCCDC167集落形成能力 46
圖 17. 以 MTT 分析MCF-7 與三株shCCDC167 生長速率 47

1.DeSantis C, Ma J, Bryan L, Jemal A. Breast cancer statistics, 2013. CA: a cancer journal for clinicians. 2014;64(1):52-62.
2.Yang G, Nowsheen S, Aziz K, Georgakilas AG. Toxicity and adverse effects of Tamoxifen and other anti-estrogen drugs. Pharmacology & therapeutics. 2013;139(3):392-404.
3.Folkerd E, Dowsett M. Sex hormones and breast cancer risk and prognosis. Breast (Edinburgh, Scotland). 2013;22 Suppl 2:S38-43.
4.Cao W, Wang X, Li JC. Hereditary breast cancer in the Han Chinese population. Journal of epidemiology. 2013;23(2):75-84.
5.Rutkowska AZ, Szybiak A, Serkies K, Rachon D. Endocrine disrupting chemicals as potential risk factor for estrogen-dependent cancers. Polskie Archiwum Medycyny Wewnetrznej. 2016;126(7-8):562-570.
6.Musgrove EA, Sutherland RL. Biological determinants of endocrine resistance in breast cancer. Nature reviews Cancer. 2009;9(9):631-643.
7.Bieche I, Parfait B, Laurendeau I, Girault I, Vidaud M, Lidereau R. Quantification of estrogen receptor alpha and beta expression in sporadic breast cancer. Oncogene. 2001;20(56):8109-8115.
8.Rojas PA, May M, Sequeira GR, et al. Progesterone Receptor Isoform Ratio: A Breast Cancer Prognostic and Predictive Factor for Antiprogestin Responsiveness. Journal of the National Cancer Institute. 2017;109(7).
9.Spector NL, Blackwell KL. Understanding the mechanisms behind trastuzumab therapy for human epidermal growth factor receptor 2-positive breast cancer. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2009;27(34):5838-5847.
10.Dawson SJ, Provenzano E, Caldas C. Triple negative breast cancers: clinical and prognostic implications. European journal of cancer (Oxford, England : 1990). 2009;45 Suppl 1:27-40.
11.Anders C, Carey LA. Understanding and treating triple-negative breast cancer. Oncology (Williston Park, NY). 2008;22(11):1233-1239; discussion 1239-1240, 1243.
12.Steiner AZ, Terplan M, Paulson RJ. Comparison of tamoxifen and clomiphene citrate for ovulation induction: a meta-analysis. Human reproduction (Oxford, England). 2005;20(6):1511-1515.
13.Todorova VK, Kaufmann Y, Luo S, Klimberg VS. Tamoxifen and raloxifene suppress the proliferation of estrogen receptor-negative cells through inhibition of glutamine uptake. Cancer chemotherapy and pharmacology. 2011;67(2):285-291.
14.Chumsri S, Howes T, Bao T, Sabnis G, Brodie A. Aromatase, aromatase inhibitors, and breast cancer. The Journal of steroid biochemistry and molecular biology. 2011;125(1-2):13-22.
15.Rhodes DR, Yu J, Shanker K, et al. ONCOMINE: a cancer microarray database and integrated data-mining platform. Neoplasia (New York, NY). 2004;6(1):1-6.
16.Rhodes DR, Kalyana-Sundaram S, Mahavisno V, et al. Oncomine 3.0: genes, pathways, and networks in a collection of 18,000 cancer gene expression profiles. Neoplasia (New York, NY). 2007;9(2):166-180.
17.Mizuno H, Kitada K, Nakai K, Sarai A. PrognoScan: a new database for meta-analysis of the prognostic value of genes. BMC medical genomics. 2009;2:18.
18.Szklarczyk D, Morris JH, Cook H, et al. The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Res. 2017;45(D1):D362-d368.
19.von Mering C, Jensen LJ, Snel B, et al. STRING: known and predicted protein-protein associations, integrated and transferred across organisms. Nucleic Acids Res. 2005;33(Database issue):D433-437.
20.Ponten F, Schwenk JM, Asplund A, Edqvist PH. The Human Protein Atlas as a proteomic resource for biomarker discovery. Journal of internal medicine. 2011;270(5):428-446.
21.Dervan EW, Chen H, Ho SL, et al. Protein macroarray profiling of serum autoantibodies in pseudoexfoliation glaucoma. Investigative ophthalmology & visual science. 2010;51(6):2968-2975.
22.Luczak M, Formanowicz D, Marczak L, et al. Deeper insight into chronic kidney disease-related atherosclerosis: comparative proteomic studies of blood plasma using 2DE and mass spectrometry. Journal of translational medicine. 2015;13:20.
23.Dodeller F, Gottar M, Huesken D, Iourgenko V, Cenni B. The lysosomal transmembrane protein 9B regulates the activity of inflammatory signaling pathways. J Biol Chem. 2008;283(31):21487-21494.
24.Zhang Y, Ran Y, Xiong Y, et al. Effects of TMEM9 gene on cell progression in hepatocellular carcinoma by RNA interference. Oncology reports. 2016;36(1):299-305.