本文選題：微小RNA + 生物信息學(xué)�。� 參考：《蘭州大學(xué)》2017年碩士論文

【摘要】：背景:顱內(nèi)腫瘤又被稱為腦腫瘤或者顱腦腫瘤,指發(fā)生于顱腔內(nèi)的神經(jīng)系統(tǒng)腫瘤,分為惡性腫瘤和良性腫瘤。根據(jù)2016年WHO中樞神經(jīng)系統(tǒng)分類概述將其分為:膠質(zhì)瘤;室管膜腫瘤;脈絡(luò)從腫瘤;神經(jīng)元和混合性神經(jīng)元-膠質(zhì)瘤;松果體區(qū)腫瘤;胚胎類腫瘤;如髓母細(xì)胞瘤;顱神經(jīng)和椎旁神經(jīng)腫瘤;腦膜瘤;間葉,非腦膜皮型腦膜瘤;黑色素細(xì)胞腫瘤;淋巴瘤;生殖細(xì)胞腫瘤;鞍區(qū)腫瘤;轉(zhuǎn)移瘤等。其中膠質(zhì)瘤又可以根據(jù)組織細(xì)胞來源分為:彌漫性星形細(xì)胞和少突膠質(zhì)細(xì)胞瘤;其他星形細(xì)胞腫瘤;室管膜腫瘤;其他膠質(zhì)瘤;神經(jīng)元和混合性神經(jīng)元-膠質(zhì)瘤等不同的類型。根據(jù)2016年最新的中樞神經(jīng)系統(tǒng)腫瘤分類建立了分子時(shí)代CNS腫瘤診斷的新概念。結(jié)合基因特征,調(diào)整部分膠質(zhì)瘤和髓母細(xì)胞瘤的的診斷。將IDH-突變型、IDH-野生型、H3 K27M-突變、IDH-突變和1p19q聯(lián)合缺失等基因特征加入膠質(zhì)瘤分級(jí)標(biāo)準(zhǔn)中。髓母細(xì)胞瘤在傳統(tǒng)的組織學(xué)分類如典型的髓母細(xì)胞瘤、多纖維性/結(jié)節(jié)增生性髓母細(xì)胞瘤、廣泛小結(jié)節(jié)性髓母細(xì)胞瘤、大細(xì)胞性髓母細(xì)胞瘤、非特指性髓母細(xì)胞瘤的基礎(chǔ)上引入分子病理特征,將WNT活化型、SHH活化型和TP53突變型、SHH活化型和TP53野生型、非WNT/非SHH活化型等分子病理特征應(yīng)用于髓母細(xì)胞瘤的分類和診斷中。III級(jí)膠質(zhì)瘤作為中樞神經(jīng)系統(tǒng)惡性腦腫瘤,主要分為間變型星形細(xì)胞瘤,IDH-突變型、間變少突神經(jīng)膠質(zhì)瘤,IDH-突變和1p19q聯(lián)合缺失型、間變型多形性黃色星形細(xì)胞瘤、間變型節(jié)細(xì)胞膠質(zhì)瘤。微小RNA(microRNA,miRNA)是存在于植物、動(dòng)物和一些病毒中小的非編碼RNA分子(含有約22個(gè)核苷酸),其在RNA沉默和基因表達(dá)的轉(zhuǎn)錄后調(diào)節(jié)中起作用。雖然大多數(shù)miRNA位于細(xì)胞內(nèi),但也已經(jīng)在細(xì)胞外環(huán)境中發(fā)現(xiàn)了一些通常稱為循環(huán)mi RNA或細(xì)胞外miRNA的miRNA分子,包括各種生物體液和細(xì)胞培養(yǎng)基。miRNA是RNA干擾的小內(nèi)源性介質(zhì),并且是有機(jī)體發(fā)育,細(xì)胞專一化和體內(nèi)平衡所需的許多生物過程的關(guān)鍵調(diào)節(jié)組分。miRNA的表達(dá)與許多嚴(yán)重疾病的生理以及病理過程相關(guān),其中包括腦腫瘤。目前尚不清楚miRNA是否與腫瘤的級(jí)別、分子亞型的特異性以及腫瘤的預(yù)后有關(guān)。到目前為止,已經(jīng)在幾乎所有種類的生物體液中發(fā)現(xiàn)了微小RNA,包括腦脊液(CSF)。許多研究已經(jīng)顯示在中樞神經(jīng)系統(tǒng)(CNS)腫瘤患者的組織以及體液中有異常表達(dá)的mi RNA,并且有學(xué)者提出miRNA可以作為中樞神經(jīng)系統(tǒng)腫瘤生物標(biāo)志物。目的:(1)通過加權(quán)基因通表達(dá)網(wǎng)絡(luò)(WGCNA)以及cytoscape軟件構(gòu)建III級(jí)膠質(zhì)瘤的無尺度共表達(dá)網(wǎng)絡(luò),探討其發(fā)生機(jī)制,尋找關(guān)鍵基因;(2)結(jié)合樣本的臨床數(shù)據(jù),找到與預(yù)后相關(guān)的miRNA和基因;(3)通過分析髓母細(xì)胞瘤差異表達(dá)的mi RNA,基于Ingenuity Pathway Analysis(IPA)軟件識(shí)別髓母細(xì)胞瘤潛在的調(diào)控網(wǎng)絡(luò)以及髓母細(xì)胞瘤發(fā)生發(fā)展過程中的關(guān)鍵信號(hào)分子;(4)基于生物信息學(xué)算法,篩選出顱內(nèi)常見腫瘤腦脊液中差異表達(dá)的miRNA。通過聚類分析,找到可以鑒別腦膜瘤、低級(jí)別膠質(zhì)瘤、膠質(zhì)母細(xì)胞瘤、轉(zhuǎn)移瘤、髓母細(xì)胞瘤以及淋巴瘤的的miRNA,選取部分miRNA分子通過熒光定量PCR技術(shù)驗(yàn)證其可靠性,從而挖掘mi RNA在腦腫瘤臨床術(shù)前診斷中的應(yīng)用價(jià)值。方法:(1)使用TCGA-Assembler下載TCGA數(shù)據(jù)庫3級(jí)RNASeqV2基因表達(dá)數(shù)據(jù),miRNA-seq數(shù)據(jù)以及樣本的臨床信息。去除表達(dá)量接近零的數(shù)據(jù),找到正常組與III級(jí)膠質(zhì)瘤差異表達(dá)的基因(different expression genes,DEG)和miRNA,使用R軟件(3.3.0)中的“DESeq”包來鑒定foldChange2.0且調(diào)整的P值0.05的差異表達(dá)基因(DEG)和miRNA。通過加權(quán)基因通表達(dá)網(wǎng)絡(luò)(WGCNA)以及cytoscape軟件構(gòu)建III級(jí)膠質(zhì)瘤的無尺度共表達(dá)網(wǎng)絡(luò),并通過基因功能GO富集以及KEGG通路分析探討其發(fā)生機(jī)制以及關(guān)鍵基因;(2)通過整合樣本的臨床數(shù)據(jù),找到與預(yù)后相關(guān)的臨床標(biāo)志物;(3)從NCBI GEO數(shù)據(jù)庫下載髓母細(xì)胞瘤mi RNA矩陣文件并執(zhí)行l(wèi)og2變換。使用線性模型和Bayes檢驗(yàn)計(jì)算差異表達(dá)基因(DEG)。利用熱圖,可視化差異表達(dá)基因。將差異表達(dá)的miRNA導(dǎo)入到IPA(Ingenuity Pathway Analysis)軟件,使用microRNA Target Filter找到靶向信息。然后使用IPA核心分析模塊分析差異表達(dá)microRNA相關(guān)的網(wǎng)絡(luò)功能;(4)從GEO數(shù)據(jù)庫下載中樞神經(jīng)系統(tǒng)腫瘤腦脊液的miRNA表達(dá)譜數(shù)據(jù),并通過R語言的limma包進(jìn)行歸一化并且尋找差異表達(dá)基因(DEG)。通過聚類分析,找到可以正確聚類樣本的mi RNA分子。最后,留取蘭州大學(xué)第二醫(yī)院神經(jīng)外科臨床中心腫瘤患者的腦脊液標(biāo)本,通過設(shè)計(jì)選定的miRNA分子,設(shè)計(jì)特異性引物,通過熒光定量PCR驗(yàn)證標(biāo)志物的可靠性。結(jié)果:(1)數(shù)據(jù)結(jié)果顯示在III級(jí)膠質(zhì)瘤中,有2036個(gè)差異表達(dá)的mRNA和50個(gè)mi RNA,并且,2036個(gè)差異基因可以聚類為5個(gè)模塊,這些模塊主要與細(xì)胞周期、有絲分裂、微管蛋白的結(jié)合、遞質(zhì)傳導(dǎo)運(yùn)輸以及p-53信號(hào)通路等有關(guān)。如在網(wǎng)絡(luò)中所示,BUB1B,KIFC1,TOP2A,BUB1,SLC12A5,ESCO2,ESPL1,EPR1,KIF15,CASC5,SGOL1,NUSAP1,CCNB2,NUF2,TTK,KIF2C在共表達(dá)網(wǎng)絡(luò)的中心。并且,BUB1B,KIFC1,TOP2A,BUB1,ESPL1,EPR1是過表達(dá)基因網(wǎng)絡(luò)的中心;SLC12A5,VSNL1,SULT4A1,TMEM130,SNAP25位于低表達(dá)基因網(wǎng)絡(luò)的中心。利用差異表達(dá)的mRNAseq和miRNAseq數(shù)據(jù)建立共表達(dá)網(wǎng)絡(luò),SLC12A5,MAL2,VSNL1,A2BP1,EPB49,SULT4A1,TMEM130,ADAM11,SNAP25,C1orf115,DNM1,SYT1位于網(wǎng)絡(luò)的中心,并且mir-128,mir-129也參與其中。我們可以假設(shè)網(wǎng)絡(luò)中心的基因就是關(guān)鍵基因并參與III級(jí)膠質(zhì)瘤的重要病理過程;(2)根據(jù)樣本的臨床數(shù)據(jù)以及標(biāo)準(zhǔn)化后的基因表達(dá)數(shù)據(jù),我們發(fā)現(xiàn)KIF4A,NCAPG,SGOL1,KLK7,SULT4A1和TSHR等基因與預(yù)后密切相關(guān)。Mir-10b,mir-27a,mir-329-1和mir-138-2等miRNA分子也與III級(jí)膠質(zhì)瘤的預(yù)后密切相關(guān);(3)根據(jù)GEO數(shù)據(jù)庫的miRNA矩陣數(shù)據(jù),我們發(fā)現(xiàn)髓母細(xì)胞瘤中48個(gè)顯著差異的表達(dá)mi RNA。IPA核心分析顯示髓母細(xì)胞瘤中28個(gè)差異表達(dá)的mi RNA與“有組織損傷和異常,生殖系統(tǒng)疾病,癌癥”調(diào)控網(wǎng)絡(luò)相關(guān),并且TP53,AGO2,ERK1/2,SIRT1和YBX1基因在髓母細(xì)胞瘤的發(fā)生發(fā)展過程中起到了重要作用;(4)根據(jù)腦脊液miRNA芯片分析,mir-205,mir-664和mir-148可以作為生物標(biāo)志物來區(qū)分轉(zhuǎn)移與其他顱內(nèi)腫瘤。MiR-21,miR-16,mi R-125b,miR-223和miR-142-3p在膠質(zhì)母細(xì)胞瘤患者腦脊液中上調(diào)。Mi R-451,mi R-142-3p,miR-25,miR-15a,mi R-16和miR-144在低級(jí)別膠質(zhì)瘤患者腦脊液中高度上調(diào)。我們認(rèn)為mir-21,mir-16在許多惡性腦腫瘤中上調(diào),與低級(jí)膠質(zhì)瘤相比,mir-125b可以是膠質(zhì)母細(xì)胞瘤或差的預(yù)后膠質(zhì)瘤的特異性生物標(biāo)志物。相對(duì)于正常和其他癌癥組,miR-711和mir-886-3p在原發(fā)性中樞神經(jīng)系統(tǒng)淋巴瘤中下調(diào)。與正常組相比,淋巴瘤組具有更低表達(dá)水平的miR-711。此外,與膠質(zhì)母細(xì)胞瘤和髓母細(xì)胞瘤相比,mir-886-3p在淋巴瘤組中下調(diào)。結(jié)論:(1)生物信息學(xué)分析為高級(jí)別膠質(zhì)瘤機(jī)制的研究提供了一種新的研究方法;(2)臨床預(yù)后研究應(yīng)該是多維度的,尤其是惡性腫瘤的預(yù)后不僅與樣本的病理分級(jí)有關(guān),更重要的是與特殊的分子或者基因標(biāo)志物密切相關(guān),并且這些信號(hào)分子可能在惡性腫瘤的發(fā)生和發(fā)展過程中起了重要作用;(3)髓母細(xì)胞瘤中,miRNA可能通過作用于TP53、AGO2、ERK1/2、SIRT1和YBX1在髓母細(xì)胞瘤的發(fā)生發(fā)展中起了重要作用;(4)MiRNA具有作為中樞神經(jīng)系統(tǒng)腫瘤非侵入性檢測標(biāo)志物的巨大潛力。但是,目前的microRNA標(biāo)志物還不能做出準(zhǔn)確的診斷。mi RNA測定似乎在淋巴瘤和轉(zhuǎn)移性腦癌的診斷中比在膠質(zhì)瘤和其他顱腦腫瘤中更敏感。一方面,仍需要基于更大樣本量的實(shí)驗(yàn)進(jìn)行更進(jìn)一步的驗(yàn)證。另一方面,隨著二代測序技術(shù)的發(fā)展,將出現(xiàn)新mi RNA分子以提高CNS疾病診斷的準(zhǔn)確性和可靠性。
[Abstract]:Background: intracranial tumors, also known as brain tumors or craniocerebral tumors, refer to neurologic tumors occurring in the cranial cavity, divided into malignant tumors and benign tumors. According to the classification of WHO central nervous system in 2016, it is divided into glioma, ependymal tumor, choroid from tumor; neurotransmitter and mixed neuron glioma; pineal region tumor; Embryoid tumors; such as medulloblastoma; cranial nerve and paravertebral nerve tumor; meningioma; interleaf, non meningocutaneous meningioma; melanocytic tumor; lymphoma; germ cell tumor; sellar tumor; metastatic tumor; among which gliomas can be divided into diffuse astrocytes and oligodendrocytes; other astrocytomas; other astrocytomas; Cell tumors; ependyma tumors; other gliomas; neurons and mixed neurons - gliomas. A new concept for the diagnosis of CNS tumors in the molecular age was established based on the latest central nervous system tumor classification in 2016. Combined with gene characteristics, the diagnosis of partial glioma and medulloblastoma was adjusted. IDH- mutant, IDH- Gene features such as wild type, H3 K27M- mutation, IDH- mutation and 1p19q joint deletion are added to the glioma grading standard. Medulloblastoma is classified as a typical medulloblastoma, fibroblastoma, nodular medulloblastoma, large cell medulloblastoma, and non special medulloblastoma in traditional histologic classification. On the basis of the cytomellus, the molecular pathological features are introduced, and the molecular pathological features such as WNT activation, SHH activation and TP53 mutation, SHH activation and TP53 wild type and non WNT/ non SHH activation type are applied to the classification and diagnosis of medulloblastoma as malignant brain tumors of the central nervous system, which are mainly divided into inter variant astrocytoma, I DH- mutant, oligodendroglioma, IDH- mutation and 1p19q joint deletion, cross variant polymorphic yellowish astrocytoma, alternating type of glioma. Small RNA (microRNA, miRNA) is a non coded RNA molecule (containing approximately 22 nucleotides) in plants, animals, and some viruses (containing about 22 nucleotides), which is silenced in RNA and gene expression. Although most of the miRNA is located in the cell, it has also found some miRNA molecules commonly known as circulating mi RNA or extracellular miRNA in the extracellular environment, including a variety of biological fluids and cell culture medium.MiRNA as a small endogenous medium for RNA interference, and is an organism development, cell specificity and body level. The expression of.MiRNA, a key regulatory component of many biological processes required, is related to the physiological and pathological processes of many serious diseases, including brain tumors. It is not clear whether miRNA is related to the tumor level, the specificity of the molecular subtype, and the prognosis of the tumor. Small RNA, including cerebrospinal fluid (CSF), has been found in the fluid. Many studies have shown the abnormal expression of MI RNA in the tissues and body fluids of the central nervous system (CNS) tumor patients, and some scholars have suggested that miRNA can be used as a biomarker for the tumor in the central nervous system. (1) through the weighted gene expression network (WGCNA) and cytoscap E software constructs a scale-free co expression network of III glioma to explore its mechanism and find key genes; (2) to find the miRNA and gene related to prognosis in combination with the clinical data of the samples; (3) the potential regulation of medulloblastoma based on Ingenuity Pathway Analysis (IPA) software is identified by analyzing the differential expression of MI RNA in medulloblastoma. Network and the key signal molecules in the development of medulloblastoma; (4) based on the bioinformatics algorithm, the differential expression of miRNA. in the cerebrospinal fluid of the common intracranial tumors was screened by clustering analysis to find miRNA for the identification of meningioma, low grade glioma, glioblastoma, metastatic tumor, medulloblastoma, and lymphoma. Some miRNA molecules are selected to verify their reliability by fluorescence quantitative PCR technology, so as to discover the value of MI RNA in the clinical diagnosis of brain tumors. (1) use TCGA-Assembler to download the 3 level RNASeqV2 gene expression data of the TCGA database, miRNA-seq data and the clinical information of the samples. The differentially expressed genes (different expression genes, DEG) and miRNA in normal group and III glioma were identified using the "DESeq" package in R software (3.3.0) to identify the differentially expressed genes of foldChange2.0 and the adjusted P value 0.05 (DEG) and the free ruler to construct a glioma. Degree co expression network, and through gene function GO enrichment and KEGG pathway analysis to explore the pathogenesis and key genes; (2) the clinical data of the integration of samples to find clinical markers related to the prognosis; (3) Download medulloblastoma mi RNA matrix files from the NCBI GEO database and perform log2 transformation. Linear model and Bayes test. Calculate the differential expression gene (DEG). Use the heat map to visualize the differentially expressed genes. Introduce the differentially expressed miRNA into the IPA (Ingenuity Pathway Analysis) software, use the microRNA Target Filter to find the target information. Then use the IPA core analysis module to analyze the differential expression microRNA related network functions; (4) download from the GEO database. The miRNA expression data of the cerebrospinal fluid of the armature nervous system were normalized and the differential expression gene (DEG) was searched through the limma package of the R language. By cluster analysis, the MI RNA molecules that could be correctly clustered were found. Finally, the cerebrospinal fluid specimens of the patients in the clinical center of the Department of Neurosurgery, Second Hospital Affiliated to Lanzhou University, were set up by the establishment of the cerebrospinal fluid specimens. The selected miRNA molecules designed specific primers and verified the reliability of the markers by fluorescence quantitative PCR. Results: (1) data showed that there were 2036 differentially expressed mRNA and 50 mi RNA in III grade gliomas, and 2036 differentially different genes could be clustered into 5 blocks. These modules were mainly divided into cell cycle, mitosis, microtubule eggs BUB1B, KIFC1, TOP2A, BUB1, SLC12A5, ESCO2, ESPL1, EPR1, KIF15, CASC5, as the center of the network. A1, TMEM130, and SNAP25 are located at the center of the low expression gene network. Using the differentially expressed mRNAseq and miRNAseq data to establish a co expression network, SLC12A5, MAL2, VSNL1, A2BP1, EPB49, SULT4A1, TMEM130, and also participate in it. We can assume the gene in the network center. (2) we found that the genes of KIF4A, NCAPG, SGOL1, KLK7, SULT4A1 and TSHR are closely related to the prognosis, and the miRNA molecules such as mir-27a, mir-329-1 and mir-138-2 are also closely related to the prognosis of gliomas based on the clinical data of the samples and the standardized gene expression data. (3) according to the miRNA matrix data of the GEO database, we found that 48 significant differences in the expression of MI RNA.IPA core analysis in medulloblastoma showed that 28 differentially expressed mi RNA in medulloblastoma were associated with "organized injury and abnormality, reproductive system disease, cancer" modulation network, and TP53, AGO2, ERK1/2, SIRT1, and YBX1 genes. It plays an important role in the development of medulloblastoma; (4) mir-205, mir-664, and mir-148 can be used as biomarkers to distinguish metastatic and other intracranial tumors from.MiR-21, miR-16, MI R-125b, miR-223 and miR-142-3p in the cerebrospinal fluid of the patients with gelatinous blastoma, according to the miRNA chip analysis of cerebrospinal fluid. MiR-25, miR-15a, MI R-16 and miR-144 are highly up-regulated in the cerebrospinal fluid of patients with low grade glioma. We think that miR-21, mir-16 is up-regulated in many malignant brain tumors. Compared with low grade gliomas, miR-125b can be a specific biomarker for glioblastoma or poor prognosis glioma. MiR-711 relative to normal and other cancer groups. And mir-886-3p was downregulated in primary CNS lymphoma. Compared with the normal group, the lymphoma group had a lower expression of miR-711.. Compared with glioblastoma and medulloblastoma, mir-886-3p was downregulated in the lymphoma group. Conclusion: (1) bioinformatics analysis provides a kind of high grade glioma mechanism. New methods of research; (2) the study of clinical prognosis should be multidimensional, especially the prognosis of malignant tumors not only related to the pathological classification of samples, but also closely related to special molecules or gene markers, and these signal molecules may play an important role in the development and development of malignant tumors; (3) medullary medullary In cytomas, miRNA may play an important role in the development of medulloblastoma by acting on TP53, AGO2, ERK1/2, SIRT1 and YBX1; (4) MiRNA has great potential as a noninvasive marker of the central nervous system tumor. However, the current microRNA markers can not make a accurate diagnosis of.Mi RNA as if in lymph nodes. The diagnosis of tumor and metastatic brain cancer is more sensitive than in gliomas and other craniocerebral tumors. On the one hand, further tests based on larger samples are still needed. On the other hand, with the development of the two generation sequencing technology, new mi RNA molecules will appear to improve the accuracy and reliability of the diagnosis of CNS disease.
【學(xué)位授予單位】：蘭州大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：R739.4

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