Recent studies have demonstrated that lncRNA can be transcribed from enhancer (enhancer lncRNA). The dysfunction of the enhancer lncRNA leads to abnormally regulate its target genes, which causes the development of cancer. Therefore, identifying and analyzing cancer-related enhancer lncRNAs is of high importance. With the comprehensive application of the next generation sequencing, the international genome projects such as TCGA and ICGC have released a lot of data. Predicting cancer-related enhancer lncRNAs by analyzing these data is helpful to biologists to select candidate lncRNAs for further experimental validation. Therefore, this project aims at proposing bioinformatics methods to analyze cancer-related high throughput data, predict cancer-related enhancer lncRNA, identify its sequence mutation and target gene, and develop a pipeline for predicting and analyzing cancer-related enhancer lncRNAs. Facing the fact that China is a high-risk country with high liver cancer occurrence rate, we plan to experimentally validate the predicted liver cancer-related enhancer lncRNAs. The completion of this project will guide the selection of candidate enhancer lncRNA for further experimental validation, and laid the foundation for uncovering the cancer mechanism and developing enhancer lncRNA-based cancer drugs.
最近的研究表明增强子可以转录出lncRNA(增强子lncRNA),功能异常的增强子lncRNA不能正常调控其靶基因,进而引发癌症, 因此,识别及分析癌症相关的增强子lncRNA具有重要意义。随着测序技术在癌症研究中的广泛应用,TCGA、ICGC等大型研究计划产生了癌症相关的海量数据,如何对这些数据进行整合及分析,准确地预测出癌症相关的增强子lncRNA是亟需解决的前沿问题。因此,本项目拟发展生物信息学方法,整合分析每种癌症相关的高通量数据,预测癌症相关的增强子lncRNA、识别其遗传变异、预测其调控的靶基因,研发一套癌症相关的增强子lncRNA识别及分析系统;针对我国是肝癌高发大国这一国情,拟对预测的肝癌相关的增强子lncRNA及其靶基因进行生物实验验证。本项目的完成可为癌生物实验准确地选取lncRNA提供依据、为揭示癌症发病机制、开发靶向增强子lncRNA的药物奠定基础。
增强子可以转录出lncRNA(增强子lncRNA),功能异常的增强子lncRNA无法正常调控其靶基因,进而引发癌症等复杂疾病, 因此,识别及分析疾病相关增强子lncRNA具有重要意义。在本项目的资助下,项目负责人及团队系统研究癌症相关的增强子lncRNA,整合分析癌症等复杂疾病相关的高通量数据,预测了肝癌等复杂疾病相关的增强子lncRNA、识别与分析了增强子lncRNA的遗传变异、调控的靶基因,研发了一套癌症等复杂疾病相关的增强子lncRNA识别及分析流程、遗传变异分析系统,为揭示癌症发病机制、开发靶向增强子lncRNA的药物奠定基础。本项目取得了较好的科研成果,共发表带标注的SCI论文28篇,其中PNAS论文6篇(SCI IF:9.5)、Nucleic Acids Research论文1篇(SCI IF:11.5)、影响因子大于5的论文15篇,培养博士生8名、硕士生6名。项目负责人在本项目的支持下,获得了国家基金委优青、黑龙江省自然科学一等奖(排名第2),完成了预期目标。
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数据更新时间:2023-05-31
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