通过共表达网络分析（WGCNA）研究前列腺癌症中的特异表达因子

发布时间：2018-06-26 22:50

本文选题：前列腺癌 + 转录组测序　；参考：《南昌大学》2014年硕士论文

【摘要】：前列腺癌是男性的世界第二大最常见的癌症，而每年的发病率有增加的趋势。所有的男性都可能罹患前列腺癌，这些情况值得引起重视。全世界范围内来说，约1/6的男性可能被诊断出前列腺癌，而在这1/6的男性中，1/36的人因此死亡。虽然，亚洲男性，，尤其是中国男性，相对于欧美男性的发病率要低很多，但是近年来中国男性的前列腺癌越来越呈多发趋势，已经成为了危害我国中老年男性的重要疾病之一。随着测序数据大规模产生，肿瘤的发生与发展，不论是在细胞水平，还是在分子水平的变化上，科学家们对此都有了更深刻的认识，即前列腺癌是一种有多基因共同作用的复杂的癌症。其中PI3K/AKT/MTOR途径，WNT途径，TGF-β/SMAD途径表达的改变，可能可以增强肿瘤细胞的生长，转移和侵袭能力，尤其是PI3K/AKT/MTOR途径，在前列腺癌中具有很重要的作用。但遗憾的是，目前科学家对于前列腺癌发生发展过程中的机制了解还不够深入。所以，研究前列腺癌与其他癌症之间的异同，可以为前列腺癌的发生发展提供重要基因水平的依据。同时，前列腺癌的早期诊断在前列腺癌的治疗中具有非常重要的临床意义。PSA（prostate specific antigen，前列腺特异抗原）是目前广泛用于检测前列腺癌的重要标志物。但是PSA并非肿瘤特异的标志物，前列腺炎症的发生也会导致PSA检测阳性。因此，我们有必要筛选出更加特异、有效的靶分子。在基因芯片，测序技术的产生，使得一次性检测成千上万个基因的表达谱成为可能。传统单基因的分析方法已经被淘汰了。而随着越来越多的数据的产生，对生物信息学分析方法提出了更高的要求，迫使科学家们必须使用生物信息学将海量的数据整合，分析，并从中筛选出合适的基因，并必须揭示海量的基因与复杂的生物学功能之间可能存在的联系。为此，本研究使用了测序，芯片的方法，结合WGCNA共表达网络分析，GO，KEGG等生物学功能数据库，试图为今后前列腺癌的研究，提供一些新的观点。【目的】本研究利用R语言中的bioconductor中的WGCNA （Weighted GeneCo-expression Network Analysis,加权基因共表达网络分析）分析包对来自于基因表达数据库GEO（Gene Expression Omnibus）中分别来源于两篇文献，共40个前列腺癌症RNA-seq数据（Gleason score6），20个前列腺癌旁组织RNA-seq数据（normal），以及16个肺癌RNA-seq数据，3个肝癌以及对应的3个癌旁组织RNA-seq数据，10个急性白血病RNA-seq数据，5个乳头状肾癌RNA-seq数据做生物信息学分析，并随后使用5种前列腺癌症常用细胞系:PrEC、PWRE、DU145、LNCaP、VCaP的RNA-seq数据进行比对。并使用了约600个affymatrix PLUS2.0A芯片数据，以及1000个TCGA RNA-SEQ测序数据进行验证。在数据比对的基础上，利用Cytoscape软件，GO,KEGG,Rectome等数据库，对数据的生物学意义进行深入分析。为了了解前列腺癌与其他组织癌症之间的关系，通过系统的研究特异表达基因的转录调控网络，以及相关的生物学通路，从而更深入的探讨前列腺癌症组织中特异表达的基因的变化以及相关的生物学特性，阐述前列腺癌症的发展的分子机制。本研究希望可以使用现有的数据库，更好的使用现有的生物信息学手段，从而发现前列腺癌中特异表达的生物标记物，探讨前列腺癌区别于其他癌症而发生发展的分子机制，因此本研究具有重要的现实意义。为进一步了解前列腺癌发生发展的分子机制以及诊断治疗提供了有用的基础研究资料。【结果】 1.前列腺癌症组织数据与前列腺癌细胞系数据之间的结果差别迥异，没有WGCNA特异表达基因modules的交集，说明细胞系与前列腺临床组织样本之间存在很大的差异。 2.从发表自cellres上的文章中的前列腺癌RNA-SEQ数据中筛选出了388个特异表达基因。从发表自PNAS上的文章中的前列腺癌RNA-SEQ数据筛选出了238个特异表达基因，其中两个集合的交集有8个基因，也就是说，在转移性前列腺癌中有8个基因是稳定的表达出来了。 3.使用芯片数据，TCGA数据进行验证，对所有特异表达结果进行了GO和KEGG网络分析。我们发现，不论在任何的前列腺癌症数据中，PI3K/Akt/mTOR途径发挥着至关重要的作用。与其同时，还发现了TGF-β/SMAD途径，黏多糖功能途径，胞外结构组织功能途径，notch途径，一些神经功能途径与PI3K途径同时发生。
[Abstract]:Prostate cancer is the second most common cancer in the world, and the incidence is increasing every year. All men are likely to suffer from prostate cancer. These are worthy of attention. Around the world, about 1/6 of men may be diagnosed with prostate cancer, and in this 1/6 male, 1/36 people die. Although, although, The incidence of Asian men, especially Chinese men, is much lower than that of men in Europe and America. However, in recent years, Chinese male prostate cancer is becoming more and more frequent and has become one of the most important diseases that endanger middle and old men in China.
With the large-scale production of sequencing data and the occurrence and development of the tumor, whether it is at the cell level or at the molecular level, the scientists have a deeper understanding that the prostate cancer is a complex cancer with multi gene interaction. The expression of the PI3K/AKT /MTOR pathway, the WNT pathway, and the TGF- beta /SMAD pathway It may enhance the growth, metastasis and invasion of tumor cells, especially the PI3K/AKT/MTOR pathway, which plays an important role in prostate cancer. But unfortunately, scientists are not well aware of the mechanism in the development of prostate cancer. So, the study of the similarities and differences between prostate cancer and other cancers can be done. It provides important gene level for the development of prostate cancer.
At the same time, the early diagnosis of prostate cancer has a very important clinical significance in the treatment of prostate cancer (prostate specific antigen, prostatic specific antigen) is an important marker for the detection of prostate cancer. But PSA is not a tumor specific marker, and the occurrence of prostatitis will also lead to the positive detection of PSA. Therefore, it is necessary for us to screen out more specific and effective target molecules.
The production of gene chips and sequencing technology makes it possible to detect the expression profiles of thousands of genes at one time. The traditional single gene analysis method has been eliminated. And as more and more data are produced, higher requirements for bioinformatics analysis have been put forward, forcing scientists to use bioinformatics. Massive data integration, analysis, and screening of appropriate genes, and must reveal the possible link between massive genes and complex biological functions.
To this end, this study uses sequencing, chip methods, combined with WGCNA to co express network analysis, GO, KEGG and other biological functional databases, trying to provide some new ideas for future research on prostate cancer.
[Objective] to use the WGCNA (Weighted GeneCo-expression Network Analysis, weighted gene co expression network analysis) in the Bioconductor of R language, the analysis packet from the gene expression database GEO (Gene Expression Omnibus) from two documents, 40 prostate cancer RNA-seq data, 20 RNA-seq data (normal), 16 RNA-seq data of lung cancer, 3 hepatoma and 3 corresponding paraplastic tissue RNA-seq data, 10 RNA-seq data for acute leukemia, 5 RNA-seq data of papillary renal carcinoma, and 5 common prostate cancer cell lines: PrEC, PWRE, DU145, LNCaP, VCaP. RNA-seq data were compared. Some 600 affymatrix PLUS2.0A chips and 1000 TCGA RNA-SEQ sequencing data were used to verify the data. On the basis of data comparison, the biological significance of the data was analyzed with Cytoscape software, GO, KEGG, Rectome and other databases. In order to understand prostate cancer and other tissue cancers The relationship between the disease and the specific expression of gene transcriptional regulatory networks and related biological pathways through systematic studies, thus further exploring the changes in genes specifically expressed in prostate cancer tissues and related biological characteristics, and explaining the molecular mechanisms of the development of prostate cancer. This study has important practical significance to further understand the molecular mechanism and diagnosis of the development of prostate cancer. Treatment provides useful basic research data.
[results]
1. the difference between the data of prostate cancer tissue and the data of the prostate cancer cell line is very different. There is no intersection of the WGCNA specific expression gene modules, which indicates that there is a great difference between the cell line and the sample of the prostatic clinical tissue.
2. the 388 specific genes were screened from the prostate cancer RNA-SEQ data published in the cellres article. 238 specific genes were screened from the prostate cancer RNA-SEQ data published in the article on PNAS, of which there were 8 genes in the intersection of two sets, that is, 8 genes were in metastatic prostate cancer. A stable expression.
3. using chip data, TCGA data, and GO and KEGG network analysis of all the specific expression results. We found that the PI3K/Akt/mTOR pathway plays a vital role in any prostate cancer data. It also found the TGF- beta /SMAD pathway, the functional pathway of the sticky polysaccharide, and the function of the extracellular structure. Pathways, Notch pathways, and some neurologic pathways occur simultaneously with the PI3K pathway.
【学位授予单位】：南昌大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：R737.25

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