异常DNA甲基化驱动的非编码RNA(lncRNA/ miRNA)协同调控癌症风险通路识别及其功能研究

Changes in the epigenetic landscape of noncoding RNA (lncRNA/ miRNA) of the cells is a critical driven factor for the initiation and progression of cancer. However, systematically identification and functional analysis of epigenetically dysregulated noncoding RNAs (ncRNAs), dissecting lncRNA/ miRNA synergistically regulated risk pathways and deciphering the underlying mechanism of cancer is a significant challenge project. From a computational systems biology perspective,in this project,we use complex disease (glioma, breast cancer and esophageal cancer) as disease models, integrates biomedical big data of high-throughput, multi-omics data generated by next-generation sequencing such as DNA-seq、MeDIP-seq、RNA-seq、Chip-seq and microarray techniques, propose computational methods for identification of cancer multiple risk biomarkers, especially identifies the epigenetically dysregulated ncRNA in cancer, further constructs DNA methylation dysregulated ncRNAs synergistically regulated biological pathways, identifies the key molecular factors and key cascade pathways of cancer, further validates the regulatory roles and the function of ncRNAs that DNA methylation dysregulated using experimental approaches, investigates the molecular mechanism of cancer, develops bioinformatics analysis platform for identifying the ncRNA diagnostic and survival prognostic markers of cancer, provides new opportunities to promote multiple molecular targets for diagnosis, treatment and prognosis of human cancer.

DNA甲基化异常驱动的非编码RNA(lncRNA/ miRNA) 调控机制改变是诱发癌症发生发展的重要因素，系统识别和鉴定癌症发生发展中表观失调的非编码RNA，识别和解析lncRNA/ miRNA协同调控通路，及其作用机制研究是具有挑战意义的课题。本课题从计算系统生物角度，以胶质瘤、乳腺癌、食管癌为疾病模型，基于新一代测序 (DNA-seq、MeDIP-seq、RNA-seq及Chip-seq)技术和芯片技术产生的高通量多组学生物医学大数据，提出癌多重风险标志物（Biomarkers）识别方法，尤其识别和鉴定癌症异常DNA甲基化驱动的非编码RNA，重构DNA甲基化异常的驱动的lncRNA/ miRNA协同调控通路，识别通路中癌关键分子、关键级联路径，进行生物学证实和癌症发病机理研究，开发癌症相关非编RNA诊断及预后分析平台，为推进癌症多分子靶点诊断、预后治疗提供新的途径。

本课题从2017年开始，经课题组成员的努力工作，已按计划于2019年底圆满完成任务，并对原课题进行扩展性工作：.我们建立与完善疾病(胶质瘤、乳腺癌等) 转录组和表观组（DNA甲基化）分子图谱，系统分析和刻画人类33种癌症甲基化调控子异常扰动的分子通路，整合lncRNA、mRNA表达谱与通路拓扑识别了疾病风险lncRNA关联的失调子通路（LncSubpathway），提出了基于全局网络扩散算法识别LncRNAs协同调控的生物学通路方法，并扩展我们的工作识别了拷贝数变异的lncRNA(lncRNAs-CNV) 及其驱动转录影响的子通路和基于人类细胞系不同染色质状态的网络motif识别癌症生物标志物及功能分析。发表在线工具Lnc2Meth (http://www.bio-bigdata.com/Lnc2Meth/)，为人类长非编码RNA和DNA甲基化研究提供了一个全面的数据资源和web工具；开发了Subpathway-GMir，整合多组学数据识别个体化抗癌药物反应的子通路特征；通过重注释CMap数据库建立lncRNA、药物和疾病之间的关联关系，构建了LNCmap数据库（http://www.bio-bigdata.com/LNCmap/）。研究工作发表在国外著名生命科学杂志《Nucleic Acids Research》、《Molecular Cancer》、《Brief Bioinform》等杂志上，共发表相关SCI论文17篇，申报软件著作权3项，专利3项，获得省级以上科研奖励2项，培养和协助培养生物信息学专业硕士研究生5名，博士研究生3名，课题组成员积极参加国内国际会议，进行了广泛的学术交流。