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Computational analysis of biological functions and pathways collectively targeted by co-expressed microRNAs in cancer

机译:共表达microRNA在癌症中共同靶向的生物学功能和途径的计算分析

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Background Multiple recent studies have found aberrant expression profiles of microRNAome in human cancers. While several target genes have been experimentally identified for some microRNAs in various tumors, the global pattern of cellular functions and pathways affected by co-expressed microRNAs in cancer remains elusive. The goal of this study was to develop a computational approach to global analysis of the major biological processes and signaling pathways that are most likely to be affected collectively by co-expressed microRNAs in cancer cells. Results We report results of computational analysis of five datasets of aberrantly expressed microRNAs in five human cancers published by the authors (pancreatic cancer) and others (breast cancer, colon cancer, lung cancer and lymphoma). Using the combinatorial target prediction algorithm miRgate and a two-step data reduction procedure we have determined Gene Ontology categories as well as biological functions, disease categories, toxicological categories and signaling pathways that are: targeted by multiple microRNAs; statistically significantly enriched with target genes; and known to be affected in specific cancers. Conclusion Our global analysis of predicted miRNA targets suggests that co-expressed miRNAs collectively provide systemic compensatory response to the abnormal phenotypic changes in cancer cells by targeting a broad range of functional categories and signaling pathways known to be affected in a particular cancer. Such systems biology based approach provides new avenues for biological interpretation of miRNA profiling data and generation of experimentally testable hypotheses regarding collective regulatory functions of miRNA in cancer.
机译:背景技术近期的多项研究发现,microRNAome在人类癌症中的异常表达谱。虽然已经通过实验确定了各种肿瘤中某些microRNA的几个靶基因,但在癌症中受共表达microRNA影响的细胞功能和途径的整体模式仍然难以捉摸。这项研究的目的是开发一种计算方法,对主要共同受癌细胞中共表达的微小RNA共同影响的主要生物学过程和信号通路进行全局分析。结果我们报告了作者(胰腺癌)和其他人(乳腺癌,结肠癌,肺癌和淋巴瘤)发表的五种人类癌症中五个异常表达的microRNA数据集的五个计算分析结果。使用组合目标预测算法miRgate和两步数据缩减程序,我们确定了基因本体论类别以及生物学功能,疾病类别,毒理学类别和信号传导途径,这些途径是:被多个microRNA靶向;统计上显着富集了靶基因;并且已知会感染特定的癌症。结论我们对预测的miRNA目标的全球分析表明,共表达的miRNA通过靶向广泛的功能类别和已知受特定癌症影响的信号通路,共同为癌细胞中异常表型的变化提供系统性的补偿性反应。这种基于生物学的系统方法为生物学解释miRNA分析数据和生成有关miRNA在癌症中的集体调节功能的实验可检验假设提供了新途径。

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