癌症非编码miRNA-lncRNA协同调控网络重构与功能特性研究

Long non-coding RNAs （lncRNAs） are a class of non-coding RNA molecules with the length of more than 200 nucleotides. They have been shown to play crucial roles in regulatory network of life activities and the development of complex diseases. Systematic identification of lncRNAs associated with complex diseases and clarifying synergistic regulation mechanisms with miRNA are still challenging. Integrating multiple high throughput data are chosen in this research, such as next generation sequencing data of lncRNA and miRNA, lncRNA array data, miRNA expression profiles, gene expression profiles and protein expression profiles. Meanwhile, a system biology approach is used to identify risk lncRNAs and miRNA associated with complex diseases and construct miRNA-lncRNA synergistic network, also, exploring synergistic regulation mechanisms and network regulatory features of non-coding RNA, furthermore, establishing Bioinformatics Analysis Approach and Platform for identifying disease lncRNAs,miRNA and regulating functional modules of miRNA-lncRNA synergistic network in complex disease. The disease related lncRNAs and functional modules in synergistic regulation would be identified in our research, that can be used to not only do further study the mechanisms of complex diseases, for example, contains Glioma, breast cancer, lung cancer, liver cancer and so on, but also provide novel insights and drug target for disease diagnosis and therapeutics. This study has important scientific and clinical value in assisting with future studies of non-coding RNA synergistic regulation and complex disease pathogenesis.

lncRNA是一类长度超过200nt的非编码RNA，在生命活动的调控网络和复杂疾病的发生发展过程中都扮演重要的角色。系统识别复杂疾病相关lncRNA和miRNA，揭示LncRNA与miRNA协同调控机制是具有挑战意义的工作。本课题从系统生物学的角度，整合lncRNA和miRNA二代测序数据、miRNA和lncRNA芯片数据、miRNA及靶基因双重表达谱和蛋白谱等高通量数据，挖掘疾病关联的lncRNA与miRNA，并重构miRNA-lncRNA协同调控网络，探索复杂疾病非编码miRNA-lncRNA的协同作用机制和网络调控特点，建立复杂疾病miRNA-lncRNA及miRNA-lncRNA-mRNA协同调控功能模块识别的生物信息学分析策略与分析平台，并应用于胶质瘤、乳腺癌、肺癌等复疾病的研究中，挖掘出的疾病特异lncRNA和miRNA-lncRNA协同调控关系为疾病的机制研究提供重要依据。

本项目按原计划完成。在项目实施过程中，融合了非编码RNA相关数据库与疾病数据库；开发了 Lnc2Cancer: 非编码RNA和人类癌症关系数据库；识别与分析复杂疾病中非编码RNA协调调控网络；剖析泛癌lncRNA-mRNA相关竞争性内源ceRNA网络；构建了泛癌中竞争性内源ceRNA-ceRNA网络全景图；系统分析恶性肿瘤中lncRNA介导的转录失调模式；基于协同的基因组变异网络揭示了12个主要癌症的分子分型；剖析了癌症Hallmark关联的候选关键lncRNA泛癌图谱。并扩展了我们的研究工作：基于lncRNA 介导的ceRNA 网络预测癌症个体化药物应答；整合lncRNA注释资源及其功能特点分析；建立人类疾病中lncRNA和DNA甲基化调控关系数据库Lnc2Meth；识别癌症基因组互斥性、遗传互作及揭示肿瘤的脆弱性等等。同时，注意成果的转化和应用，建立多项平台：lncRNA的功能、基因组特征、表达和组蛋白修饰等多个方面的注释资源LNCat（http://biocc.hrbmu.edu.cn/LNCat/）；人类lncRNA和DNA甲基化研究的数据资源和web工具Lnc2Meth (http://www.bio-bigdata.com /Lnc2Meth/)；癌症单细胞功能异质性资源平台CancerSEA（http://biocc.hrbmu.edu.cn/CancerSEA）； lncRNA、药物和疾病之间的关联关系数据库LNCmap（http://www.bio-bigdata.com/LNCmap/）。研究工作发表在《Nucleic Acids Research》、《Briefings in Bioinformatics》、《Cancer Research》等杂志上，发表SCI论文63篇，培养了30余名学生。研究成果为癌症的诊断和治疗提供了理论依据，具有潜在的社会效益和经济价值。

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