【摘要】：癌癥是一種復雜的疾病,通常由多個癌基因驅動形成。隨著生物信息學和生物技術的不斷發(fā)展,從癌癥患者基因組信息的角度入手,開發(fā)新型算法,實現(xiàn)針對一組病患或人群的精準治療,已經成為癌癥治療的新思路。乳腺癌是女性發(fā)病率最高的癌癥,其中三陰性乳腺癌因為目前仍然沒有找到合適的治療靶點,成為乳腺癌研究的焦點和難點。為了更好地實現(xiàn)精準醫(yī)療,解決三陰性乳腺癌沒有合適治療靶點的問題,本文利用實驗室新開發(fā)的算法State specific network Inference via Mutually exclusive Bimodality Analysis(SIMBA),研發(fā)腫瘤生物標記物。我們首次將其應用到前列腺癌中關鍵轉錄因子調控micro RNAs的研究中進行算法合理性的驗證。在此基礎上,我們又將新型算法應用到了三陰性乳腺癌的研究中,我們成功的找到了在三陰性乳腺癌中發(fā)揮協(xié)同作用的關鍵轉錄因子EN1和FOXC1,并利用生物學實驗驗證了計算挖掘的關鍵轉錄因子作為三陰性乳腺癌新的生物標記物的重要性。綜上,我們采用精準醫(yī)療的理念開發(fā)了用于尋找腫瘤生物標記物的新型算法,并將其應用到前列腺癌中進行驗證,并將其應用到了三陰性乳腺癌尋找聯(lián)合生物標記物的研究中,并得到了在三陰性乳腺癌中發(fā)揮重要協(xié)同作用的關鍵轉錄因子EN1和FOXC1,為后續(xù)臨床研發(fā)抗癌的小分子靶點藥物提供了新的思路。
[Abstract]:Cancer is a complex disease, usually driven by multiple oncogenes. With the development of bioinformatics and biotechnology, from the perspective of genome information of cancer patients, it has become a new way of cancer treatment to develop new algorithms to achieve accurate treatment for a group of patients or groups of people. Breast cancer is the most common cancer in women. Three-negative breast cancer has become the focus and difficulty of breast cancer research because it still has no suitable treatment target. In order to achieve accurate medical treatment and solve the problem that there is no suitable target for triple negative breast cancer, a new laboratory algorithm, State specific network reference via complementary exclusive imodulation Analysis (Simba), is used to develop tumor biomarkers. We used it for the first time in the study of key transcription factors regulating micro RNAs in prostate cancer to verify the rationality of the algorithm. On this basis, we applied the new algorithm to the study of triple-negative breast cancer. We have successfully identified the key transcription factors EN1 and FOXC1 which play a synergistic role in triple-negative breast cancer and verified the importance of the key transcription factors as a new biomarker for triple-negative breast cancer by biological experiments. To sum up, we developed a new algorithm for finding tumor biomarkers based on the concept of precision medicine, and applied it to prostate cancer for verification, and applied it to the study of tri-negative breast cancer looking for combined biomarkers. The key transcription factors EN1 and FOXC1 which play an important synergistic role in tri-negative breast cancer were obtained.
【學位授予單位】：中國科學院大學(中國科學院上海藥物研究所)
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R96

【參考文獻】

相關期刊論文 前2條

1 ;Targeting Gene-Virotherapy of Cancer and its prosperity[J];Cell Research;2006年11期

2 ;Targeting gene-virotherapy of cancer[J];Cell Research;2006年08期

，

本文編號：2119112