本文關(guān)鍵詞： 卵巢上皮癌 多藥耐藥 蛋白組學(xué) 代謝組學(xué) 血清　出處：《廣西醫(yī)科大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：目的使用蛋白組學(xué)及代謝組學(xué)技術(shù)研究卵巢上皮癌多藥耐藥患者血清中差異表達(dá)的蛋白質(zhì)及代謝化合物，，尋找卵巢上皮癌多藥耐藥相關(guān)的診斷標(biāo)志物及探索多藥耐藥的發(fā)病機(jī)制，進(jìn)而找到逆轉(zhuǎn)耐藥治療的靶點(diǎn)。 方法收集臨床上卵巢上皮癌（EOC）鉑類耐藥患者（PTR）、非耐藥患者（PTS）、卵巢良性囊腫（BOC）及正常健康人（NC）四組血清各10例，每組的10例樣品混合成一個(gè)pool，使用Human14親和柱去除血清中高豐度蛋白后，收集去除高豐度蛋白后的組分用于蛋白組學(xué)的分析。本實(shí)驗(yàn)采用基于iTRAQ的蛋白組學(xué)技術(shù)分析不同分組血清差異蛋白表達(dá)譜，然后借助生物信息學(xué)方法篩選出有重要價(jià)值的蛋白質(zhì)，采用Western blot及ELISA技術(shù)驗(yàn)證其表達(dá)的規(guī)律；此外，從蛋白組學(xué)分析的樣本中抽取132例臨床血清樣本，包括PTR、PTS、BOC及NC四組，利用液質(zhì)聯(lián)用正離子模式檢測(cè)四組血清代謝指紋譜。 結(jié)果兩次iTRAQ實(shí)驗(yàn)總共鑒定三百多種蛋白，本研究對(duì)四組樣本中兩兩進(jìn)行對(duì)比分析，重點(diǎn)關(guān)注PTS及PTR間的差異表達(dá)，兩組鑒定到62個(gè)有統(tǒng)計(jì)學(xué)意義的差異表達(dá)蛋白，使用生物信息學(xué)方法對(duì)這62個(gè)蛋白進(jìn)行全面分析，并采用Western blot及ELISA技術(shù)對(duì)部分差異蛋白進(jìn)行驗(yàn)證，表達(dá)趨勢(shì)與質(zhì)譜一致。代謝組學(xué)共檢測(cè)到25800個(gè)代謝化合物，使用主成分分析（PCA）對(duì)數(shù)據(jù)降維后，并結(jié)合臨床資料進(jìn)行分析后得到6個(gè)對(duì)EOC多藥耐藥意義重大的差異代謝物。 結(jié)論差異表達(dá)蛋白SERPINA1、FN1、ORM1及6個(gè)差異代謝物可對(duì)EOC化療的療效起到監(jiān)測(cè)作用，可能參與EOC多藥耐藥的生物過程，是EOC多藥耐藥潛在的診斷標(biāo)志物及逆轉(zhuǎn)耐藥治療藥物的作用靶點(diǎn)。
[Abstract]:The purpose of using protein and metabolic compounds of proteomics and metabolomics technology of differential expression of epithelial ovarian cancer multidrug resistance in the serum of patients with epithelial ovarian cancer, looking for multidrug resistance related markers and explore the pathogenesis of multidrug resistance, and then find the target for drug resistance reversal treatment.
Methods clinical on epithelial ovarian cancer (EOC) patients with platinum resistant (PTR), non resistant patients (PTS), benign ovarian cyst (BOC) and healthy people (NC) between the four groups in all 10 cases, each of the 10 samples are mixed into a pool, use the Human14 affinity column to remove high abundant proteins the serum collected after removing high abundance proteins after the component is used for the analysis of proteomics. In this experiment, the protein iTRAQ of serum protein expression profile differences in different groups based on, and with the help of screening valuable protein bioinformatics methods, using Western blot and ELISA technology to verify the expression of the law; in addition, from proteomic analysis in samples from 132 cases of clinical serum samples, including PTR, PTS, BOC and NC four groups, combined with positive ion mode detection of serum metabolic fingerprinting using four groups of fluid.
The results of the two experiment iTRAQ a total of more than 300 proteins identified in this study, 22 of four samples were analyzed, focusing on the PTS expression and PTR protein expression in 62, there was a significant difference between the two groups identified using bioinformatics methods to analyze the 62 egg white, and validation of some proteins by Western blot and ELISA technology, expressed the same trend with mass spectrometry. Metabonomics detected a total of 25800 metabolic compounds, using principal component analysis (PCA) to reduce the dimensionality of the data, and combined with clinical data were analyzed after 6 significant differences on EOC multidrug resistant metabolites.
Conclusion differentially expressed proteins SERPINA1, FN1, ORM1 and 6 differential metabolites can play a monitoring role in the efficacy of EOC chemotherapy. They may be involved in the biological process of EOC multidrug resistance. It is a potential diagnostic marker for EOC multidrug resistance and a target for reversing drug-resistant drugs.

【學(xué)位授予單位】：廣西醫(yī)科大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：R737.31

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