本文選題：生物信息學(xué)　切入點(diǎn)：基因　出處：《第二軍醫(yī)大學(xué)》2017年碩士論文　論文類型：學(xué)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(jìn)入二十一世紀(jì)以來,隨著生物技術(shù)的進(jìn)步和對腫瘤機(jī)制的深入探索,靶向抗腫瘤療法開始應(yīng)用于臨床,成為現(xiàn)代醫(yī)學(xué)中最強(qiáng)大的治療和診斷工具,在腫瘤學(xué)領(lǐng)域也變得越來越重要。單克隆抗體靶向抗腫瘤藥物本質(zhì)上是一類修飾蛋白,以腫瘤細(xì)胞特定部位為靶點(diǎn),專門抑制在腫瘤生長中的信號通路,誘導(dǎo)腫瘤細(xì)胞產(chǎn)生免疫應(yīng)答,從而選擇性殺傷腫瘤細(xì)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(yīng)癥狀,如胃腸道毒性、心血管毒性和皮膚毒性反應(yīng)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(guān)文獻(xiàn)綜述分析,很少就單抗藥物不良反應(yīng)的發(fā)生機(jī)制進(jìn)行探究。有研究表明,基因和不良反應(yīng)之間有一定的關(guān)聯(lián)性,然而關(guān)于此類研究主要是借助藥物流行病學(xué)研究或分子生物學(xué)研究進(jìn)行,往往投入大量人力物力財力。當(dāng)前已有生物信息學(xué)課題組開始進(jìn)行基因相關(guān)的藥物不良反應(yīng)研究,但主要以收集所有上市藥物并建立相關(guān)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(xué)手段對單克隆抗體靶向抗腫瘤藥物的基因--不良反應(yīng)關(guān)聯(lián)性進(jìn)行挖掘研究,意在探索基因--不良反應(yīng)關(guān)聯(lián)關(guān)系研究的新思路,為分子生物學(xué)和藥物流行病學(xué)的進(jìn)一步研究提供理論基礎(chǔ),為單克隆抗體靶向抗腫瘤藥物的不良反應(yīng)研究提供初步參考。研究方法:本研究通過文獻(xiàn)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(yīng)關(guān)聯(lián)關(guān)系數(shù)據(jù),來構(gòu)建藥物--基因--不良反應(yīng)關(guān)聯(lián)關(guān)系網(wǎng)絡(luò),然后聯(lián)合關(guān)聯(lián)規(guī)則挖掘算法和頻數(shù)法(ROR、PRR、χ2、MHRA和Yule’s Q)進(jìn)行信號挖掘,根據(jù)挖掘結(jié)果篩選出高關(guān)聯(lián)信號進(jìn)行深入分析。數(shù)據(jù)統(tǒng)計采用EXEL 2010進(jìn)行計算。研究結(jié)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(yīng)數(shù)據(jù)記錄1151條,構(gòu)建一一對應(yīng)的基因--藥物--不良反應(yīng)網(wǎng)絡(luò)共60258條。2、關(guān)聯(lián)規(guī)則算法作用度設(shè)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(guān)聯(lián)規(guī)則算法挖掘結(jié)果篩選出4個基因--不良反應(yīng)關(guān)聯(lián)信號較強(qiáng)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(guān)聯(lián)規(guī)則算法和頻數(shù)法(Yule’s Q、PRR、ROR、χ2)挖掘結(jié)果中信號強(qiáng)度和重合度較高的基因--不良反應(yīng)配對結(jié)合相關(guān)的藥物進(jìn)行分析,分別是阿柏西普各部位出血不良反應(yīng)研究、派姆單抗皮膚不良反應(yīng)研究和西妥昔單抗呼吸系統(tǒng)不良反應(yīng)研究。研究結(jié)論:本研究構(gòu)建了單克隆抗體靶向抗腫瘤藥物--基因--不良反應(yīng)關(guān)聯(lián)關(guān)系網(wǎng)絡(luò),聯(lián)合運(yùn)用關(guān)聯(lián)規(guī)則挖掘算法和頻數(shù)法進(jìn)行信號挖掘;對比關(guān)聯(lián)規(guī)則算法和頻數(shù)法信號挖掘結(jié)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(yīng)關(guān)聯(lián)信號較強(qiáng)的藥物;通過文獻(xiàn)檢索和數(shù)據(jù)庫查詢,對高關(guān)聯(lián)信號進(jìn)行分析,發(fā)現(xiàn)信號挖掘結(jié)果對后續(xù)研究有一定的參考性;本研究屬于基礎(chǔ)研究,為藥物流行病學(xué)研究和單克隆抗體靶向抗腫瘤藥物不良反應(yīng)的進(jìn)一步研究提供了初步的數(shù)據(jù)參考和理論基礎(chǔ)。
[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(xué)位授予單位】：第二軍醫(yī)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：R979.1

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