本文選題：生物信息學　切入點：基因　出處：《第二軍醫(yī)大學》2017年碩士論文　論文類型：學位論文

【摘要】：近年來,由于惡性腫瘤發(fā)病率和腫瘤全球化趨勢不斷上升,人類的生命健康安全飽受威脅,而傳統(tǒng)的化療藥物在癌癥治療中存在耐藥性、療效低且毒副作用大等各種缺陷。進入二十一世紀以來,隨著生物技術的進步和對腫瘤機制的深入探索,靶向抗腫瘤療法開始應用于臨床,成為現(xiàn)代醫(yī)學中最強大的治療和診斷工具,在腫瘤學領域也變得越來越重要。單克隆抗體靶向抗腫瘤藥物本質上是一類修飾蛋白,以腫瘤細胞特定部位為靶點,專門抑制在腫瘤生長中的信號通路,誘導腫瘤細胞產生免疫應答,從而選擇性殺傷腫瘤細胞,相對于傳統(tǒng)化療藥物有著高效低毒的優(yōu)勢,但隨著臨床使用增加,也表現(xiàn)出各種副反應癥狀,如胃腸道毒性、心血管毒性和皮膚毒性反應等。目前對于單抗類靶向抗腫瘤藥物的研究也主要是臨床用藥的案例報道和相關文獻綜述分析,很少就單抗藥物不良反應的發(fā)生機制進行探究。有研究表明,基因和不良反應之間有一定的關聯(lián)性,然而關于此類研究主要是借助藥物流行病學研究或分子生物學研究進行,往往投入大量人力物力財力。當前已有生物信息學課題組開始進行基因相關的藥物不良反應研究,但主要以收集所有上市藥物并建立相關模型和數(shù)據(jù)庫為主,缺乏對某類藥物的具體研究。研究目的:鑒于以上研究現(xiàn)狀,本研究采用生物信息學手段對單克隆抗體靶向抗腫瘤藥物的基因--不良反應關聯(lián)性進行挖掘研究,意在探索基因--不良反應關聯(lián)關系研究的新思路,為分子生物學和藥物流行病學的進一步研究提供理論基礎,為單克隆抗體靶向抗腫瘤藥物的不良反應研究提供初步參考。研究方法:本研究通過文獻檢索、數(shù)據(jù)庫查詢,收集單抗類藥物--基因作用信息和藥物--不良反應關聯(lián)關系數(shù)據(jù),來構建藥物--基因--不良反應關聯(lián)關系網絡,然后聯(lián)合關聯(lián)規(guī)則挖掘算法和頻數(shù)法(ROR、PRR、χ2、MHRA和Yule’s Q)進行信號挖掘,根據(jù)挖掘結果篩選出高關聯(lián)信號進行深入分析。數(shù)據(jù)統(tǒng)計采用EXEL 2010進行計算。研究結果:1、本研究共納入14個單克隆抗體靶向抗腫瘤藥物,收集到藥物--基因相互作用信息記錄638條,藥物--不良反應數(shù)據(jù)記錄1151條,構建一一對應的基因--藥物--不良反應網絡共60258條。2、關聯(lián)規(guī)則算法作用度設為Lift2時,共檢出信號829個,相對Yule’s Q、PRR、ROR、χ2、MRHA檢出信號重合率分別為73.95%、57.39%、57.39%、24.65%、3.81%.3、關聯(lián)規(guī)則算法挖掘結果篩選出4個基因--不良反應關聯(lián)信號較強的藥物,分別是阿柏西普,派姆單抗,納武單抗,西妥昔單抗。4、篩選關聯(lián)規(guī)則算法和頻數(shù)法(Yule’s Q、PRR、ROR、χ2)挖掘結果中信號強度和重合度較高的基因--不良反應配對結合相關的藥物進行分析,分別是阿柏西普各部位出血不良反應研究、派姆單抗皮膚不良反應研究和西妥昔單抗呼吸系統(tǒng)不良反應研究。研究結論:本研究構建了單克隆抗體靶向抗腫瘤藥物--基因--不良反應關聯(lián)關系網絡,聯(lián)合運用關聯(lián)規(guī)則挖掘算法和頻數(shù)法進行信號挖掘;對比關聯(lián)規(guī)則算法和頻數(shù)法信號挖掘結果,發(fā)現(xiàn)兩類方法的重合度較好;篩選出4個基因--不良反應關聯(lián)信號較強的藥物;通過文獻檢索和數(shù)據(jù)庫查詢,對高關聯(lián)信號進行分析,發(fā)現(xiàn)信號挖掘結果對后續(xù)研究有一定的參考性;本研究屬于基礎研究,為藥物流行病學研究和單克隆抗體靶向抗腫瘤藥物不良反應的進一步研究提供了初步的數(shù)據(jù)參考和理論基礎。
[Abstract]:In recent years, the trend of malignant tumor incidence and tumor globalization rising, threatened human health and safety, while the traditional chemotherapy drugs resistance existed in the treatment of cancer, curative effect and low toxic side effects and other defects. Since twenty-first Century, with the progress of biotechnology and to explore the mechanism of tumor target. Begin to be applied in clinical anti-tumor therapy, treatment and become the most powerful diagnostic tools in modern medicine, has become more and more important in the field of oncology. Monoclonal antibody targeted anticancer drugs are essentially a class of modified proteins to specific parts of tumor cell targeting inhibition in the pathway of tumor growth specifically, the immune response induced by tumor cells, thereby selectively killing tumor cells, compared with the traditional chemotherapy drugs have the advantages of high efficiency and low toxicity, but with the increase of clinical use, Also exhibit various side effects such as gastrointestinal symptoms, toxicity, cardiovascular toxicity and skin toxicity. The monoclonal antibody targeting of anticancer drugs is mainly clinical case report and literature review analysis, little adverse reaction mechanism of monoclonal antibody drugs are explored. Studies have shown that there is association certain between genes and adverse reactions, however, about this kind of research is mainly carried out by the study of epidemiological studies of molecular biology or medicine, often put a lot of manpower and material resources. The current bioinformatics research group began to study the adverse drug reaction related genes, but mainly to collect all the listed drugs and establish the related model and database. The lack of specific research, for a certain class of drugs. Objective: in view of the above research, this study uses bioinformatics means of single Research on mining cloning antibody targeted antitumor drug adverse reaction gene relevance, to explore new ideas for gene -- Study on the relationship between the adverse reactions, and provide a theoretical basis for further research on the molecular biology and drug epidemiology, provide preliminary reference for monoclonal antibody targeting study of adverse reactions of antitumor drugs. Methods: This study through literature search, database query, collection of monoclonal antibody drugs -- gene information and drug adverse reaction -- correlation data, to construct the drug adverse reaction gene association network, then the joint association rule mining algorithm and frequency method (ROR, PRR, MHRA and Yule was 2, s Q) signal according to the mining, mining results screened high correlation signal were analyzed. Data were analyzed by EXEL 2010 were calculated. Results: 1. This study included 14 monoclonal antibody Body targeted anticancer drugs, collected drug -- gene interaction information records 638, drug adverse reaction data record 1151, a total of 60258.2 gene -- drug adverse reaction network correspondence, association rules algorithm is set to Lift2, there were 829 signals, Yule 's Q, PRR, ROR, 2, MRHA positive signal coincidence rate were 73.95%, 57.39%, 57.39%, 24.65%, 3.81%.3, the algorithm of association rules mining results screened 4 genes -- adverse reactions associated signals strong drugs, are eylea, Wu Na paim monoclonal antibody, monoclonal antibody, cetuximab and.4. Screening of association rules algorithm and frequency method (Yule' s Q, PRR, ROR, 2) - gene mining results in the adverse reactions of signal strength and a high degree of coincidence of the paired with related analysis of drug adverse reactions, respectively study the various parts eylea bleeding, skin paim monoclonal antibody Study on the adverse reactions and adverse reactions of cetuximab in the respiratory system. The conclusion of the study: This study established a monoclonal antibody targeting antitumor drugs -- gene - adverse reaction relationship network, combined with the association rules mining algorithm and frequency method for signal comparison mining; association rule algorithm and frequency signal mining results, found two the method of coincidence degree is better; screened 4 genes -- strong signal drug adverse reaction incidence; through the literature search and database query, the high correlation of signal analysis, found that the signal mining results to further research have certain reference; this research belongs to the basic research, provides preliminary data reference and theoretical basis for the further research on drug epidemiology research and monoclonal antibody targeted antitumor drug adverse reaction.

【學位授予單位】：第二軍醫(yī)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R979.1

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