本文選題：肺腺癌 + miRNAs��； 參考：《南京醫(yī)科大學》2017年碩士論文

【摘要】：第一部分基于TCGA數(shù)據(jù)庫構(gòu)建肺腺癌預后相關的microRNA風險模型目的:肺癌是全球范圍內(nèi)腫瘤致死的首要因素,盡管近年來診斷方法及治療手段有了較大的提高,其預后仍然沒有得到顯著的改善。miRNAs(microRNAs,微小RNAs)是一類短小非編碼RNAs,能夠在轉(zhuǎn)錄后水平發(fā)揮重要的調(diào)控作用,其異常表達參與了腫瘤的發(fā)生與發(fā)展。越來越多的證據(jù)表明,miRNAs有望成為新的腫瘤標志物,包括腫瘤的預后。本研究旨在尋找LUAD(lung adenocarcinoma,肺腺癌)特異性的預后相關miRNAs,為LUAD患者的預后預測及個性化治療方案的制定奠定一定的工作基礎。方法:1.下載TCGA腫瘤數(shù)據(jù)庫中522例LUAD患者的miRNA-Seq數(shù)據(jù)及詳細的臨床數(shù)據(jù),并進行LUAD組織與癌旁正常組織中差異miRNAs分析。2.將患者隨機分為訓練集及測試集,在訓練集中利用LASSOCOX回歸模型進行LUAD預后相關miRNAs的篩選,并構(gòu)建基于miRNAs表達譜的線性風險模型預測患者的預后。3.分別在測試集和總體樣本中對風險模型預測患者預后的有效性進行驗證。4.單因素及多因素COX回歸分析miRNAs風險模型與其他臨床變量的相關性。結(jié)果:1.相比于癌旁正常組織,LUAD組織中共篩出72個顯著差異表達的miRNAs(差異表達倍數(shù)2,且調(diào)整后的P值0.05),其中表達量上調(diào)的miRNAs有45個,表達量下調(diào)的miRNAs有27個。2.在訓練集中確定了 7個與LUAD患者總生存期相關的miRNAs,并基于7個miRNAs構(gòu)建了預后風險模型,風險評分=(-0.109×miR-101-3p的表達量)+(-0.455×miR-148a-3p 的表達量)+(0.146×miR-192-5p 的表達量)+(0.179×miR-193b-3p 的表達量)+(0.383×miR-505-3p 的表達量)+(0.212×miR-584-5p 的表達量)+(-0.06×miR-99a-5p 的表達量)。3.在訓練集、測試集及總體樣本中,高風險組患者與低風險組患者相比總體生存時間均顯著降低(所有P值0.05)。4.多因素COX回歸分析顯示,風險模型在訓練集、測試集及總體樣本中均是一個獨立的預后因子(訓練集:HR=1.97,P=0.02;測試集:HR=1.927,P=0.009;總體:HR=1.909,P=0.001)。結(jié)論:1.miR-101-3p、miR-148a-3p 及 miR-99a-5p 與 LUAD 患者的預后呈正相關;miR-192-5p、miR-193b-3p、miR-505-3p 及 miR-584-5p 與 LUAD 患者的預后呈負相關。2.基于以上7個miRNAs構(gòu)建的風險模型能夠很好地將LUAD患者分為預后不良的高風險組和低風險組,且獨立于患者臨床變量預測患者的預后。第二部分MiR-101-3p靶向TGFA在肺腺癌中發(fā)揮抑癌作用的初步研究目的:異常表達的miRNAs在腫瘤中發(fā)揮著雙重作用,既能促進又能抑制腫瘤的發(fā)生與發(fā)展,同時與其靶基因共同構(gòu)成了一個復雜的網(wǎng)絡調(diào)控著腫瘤的進展。越來越多的證據(jù)表明miR-101-3p在腫瘤中呈異常表達的狀態(tài),包括LUAD。然而,miR-101-3p在LUAD中的功能及其潛在的分子機制仍需進一步闡明。方法:1.下載TCGA及GEO數(shù)據(jù)庫中LUAD相關的miRNAs測序及芯片數(shù)據(jù),整合分析miR-101-3p在LUAD組織中的表達水平。2.采用熒光定量PCR技術在細胞水平驗證miR-101-3p的表達水平。3.采用CCK-8、克隆形成、細胞劃痕、Transwell細胞侵襲實驗檢測過表達miR-101-3p后LUAD細胞增殖、遷移及侵襲等生物學功能的變化。4.采用TargetScan、miRanda、PITA及RNA22四個靶基因預測數(shù)據(jù)庫對miR-101-3p的靶基因進行預測,并對靶基因進行功能及通路的富集分析,以確定miR-101-3p的最佳下游靶基因。5.運用熒光定量PCR技術及western blot技術在RNA及蛋白水平檢測過表達miR-101-3p后TGFA的表達水平變化。6.利用TCGA及Kaplan-Meier plotter兩個數(shù)據(jù)庫分別分析TGFA在LUAD組織中的表達水平,及其與LUAD患者預后的相關性。結(jié)果:1.在 TCGA 及 3 個 GEO 數(shù)據(jù)集(GSE74190、GSE51853、GSE48414)中,與正常肺組織相比,LUAD組織中的miR-101-3p均呈顯著低表達狀態(tài)(所有P值0.001)。2.與正常肺上皮細胞BEAS-2B相比,LUAD細胞株A549及H1299中的miR-101-3p均呈顯著低表達狀態(tài)(所有P值0.001)。3.過表達miR-101-3p后LUAD細胞A549的增殖、遷移及侵襲能力均受到了顯著的抑制(P0.05)。4.TGFA作為miR-101-3p的最佳預測靶標,在過表達miR-101-3p后,其RNA水平及蛋白水平均顯著下調(diào)(P0.01)。5.LUAD組織中TGFA呈高表達狀態(tài),且高表達的TGFA與患者的不良預后相關(HR:1.44;P=0.0023)。結(jié)論:miR-101-3p在LUAD中能夠通過靶向調(diào)節(jié)TGFA抑制LUAD細胞的增殖、遷移及侵襲。
[Abstract]:The first part is based on the TCGA database to construct the microRNA risk model related to the prognosis of lung adenocarcinoma. Lung cancer is the leading factor in cancer death worldwide. Although the diagnostic methods and treatment methods have been greatly improved in recent years, the prognosis is still not significantly improved,.MiRNAs (microRNAs, small RNAs) is a class of short and non coding. RNAs can play an important regulatory role at post transcriptional levels, and its abnormal expression is involved in the occurrence and development of tumors. More and more evidence suggests that miRNAs is expected to become a new tumor marker, including the prognosis of the tumor. This study aims to find the specific prognosis associated miRNAs for LUAD (lung adenocarcinoma, lung adenocarcinoma), for LUAD patients Prognosis prediction and the formulation of individualized treatment plan lay a certain work basis. Methods: 1. download the miRNA-Seq data and detailed clinical data of 522 cases of LUAD patients in the TCGA tumor database, and carry out the difference miRNAs analysis between the LUAD tissue and the normal tissue adjacent to the cancer, and randomly divide the patients into training set and test set, and use LA in training to concentrate on the training set. The SSOCOX regression model was used to screen the prognosis related miRNAs for LUAD and to construct a linear risk model based on miRNAs expression to predict the prognosis of patients..3. was used to verify the effectiveness of the prognosis of patients in the test set and the overall sample, respectively. The.4. single factor and the multiple factor COX regression analysis of the miRNAs risk model and other clinical changes were carried out. Results: 1. compared with para cancerous normal tissue, 72 significant differentially expressed miRNAs were screened in LUAD tissue (differential expression multiple 2, and adjusted P 0.05), of which 45 expressed miRNAs, and 27.2. in miRNAs expression determined 7 miRNAs associated with the total survival of LUAD patients in the training set. And based on 7 miRNAs, the prognosis risk model was constructed, the risk score = (-0.109 x miR-101-3p expression) + (-0.455 x miR-148a-3p expression) + (0.146 x miR-192-5p expression) + (the expression of 0.179 * miR-193b-3p) + + (0.212 x miR-584-5p expression) + (-0.06 * miR-99a-5p expression).3. is In the training set, the test set and the overall sample, the overall survival time of the patients in the high risk group was significantly lower than the low risk group (all P value 0.05).4. multiple factor COX regression analysis showed that the risk model was an independent prefactor in the training set, the test set and the overall sample (training set: HR=1.97, P=0.02; test set: HR=1.927, P=0 .009; overall: HR=1.909, P=0.001). Conclusion: 1.miR-101-3p, miR-148a-3p and miR-99a-5p are positively correlated with the prognosis of patients with LUAD; miR-192-5p, miR-193b-3p, miR-505-3p and miR-584-5p are negatively correlated with the prognosis of patients with LUAD. The risk group and the low risk group are independent of the patient's clinical variables to predict the prognosis of the patient. Second part second the preliminary study on the inhibitory effect of TGFA on lung adenocarcinoma: the abnormal expression of miRNAs plays a double role in the tumor, which can both promote and inhibit the occurrence and development of the tumor, and co construct with its target gene. A complex network regulates the progress of cancer. More and more evidence shows that miR-101-3p is abnormal in tumor, including LUAD., however, the function of miR-101-3p in LUAD and its potential molecular mechanism still need to be further clarified. Method: 1. download LUAD related miRNAs sequencing and chip data in TCGA and GEO database. Integrated analysis of the expression level of miR-101-3p in LUAD tissues.2. using fluorescence quantitative PCR technique to verify the expression level of miR-101-3p at the level of miR-101-3p using CCK-8, cloned formation, cell scratch, and Transwell cell invasion test to detect the proliferation of LUAD cells after miR-101-3p, migration and invasion of LUAD cells,.4. adopt Targe Four target gene prediction databases of tScan, miRanda, PITA and RNA22 were used to predict the target genes of miR-101-3p, and the function and pathway of the target genes were enriched and analyzed to determine the best downstream target gene of miR-101-3p.5. using fluorescence quantitative PCR technology and Western blot technology to detect the expression of miR-101-3p after RNA and protein levels. .6. using two databases of TCGA and Kaplan-Meier plotter to analyze the expression level of TGFA in LUAD tissue and the correlation with the prognosis of LUAD patients. Results: 1. in TCGA and 3 GEO datasets (GSE74190, GSE51853, GSE48414), compared with normal lung tissue, the expressions in the tissues were significantly lower. The state (all P 0.001).2. compared with the normal lung epithelial cell BEAS-2B, the miR-101-3p in the LUAD cell line A549 and H1299 showed significant low expression (all P value 0.001).3. overexpression miR-101-3p after LUAD cell A549 proliferation, migration and invasion ability were significantly inhibited as the best prediction target, After overexpression of miR-101-3p, the level of RNA and protein decreased significantly (P0.01) in.5.LUAD tissues, and the high expression of TGFA was associated with the poor prognosis of the patients (HR:1.44; P=0.0023). Conclusion: miR-101-3p in LUAD can inhibit the proliferation, migration and invasion of LUAD cells by targeting regulation TGFA.

【學位授予單位】：南京醫(yī)科大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R734.2

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本文編號：1773469