NICTA, Victoria Laboratory, Department of Computer Science and Software Engineering, University of Melbourne, VIC 3010, Australia.
Bioinformatics. 2010 Jan 15;26(2):161-7. doi: 10.1093/bioinformatics/btp654. Epub 2009 Nov 23.
Cancer evolves through microevolution where random lesions that provide the biggest advantage to cancer stand out in their frequent occurrence in multiple samples. At the same time, a gene function can be changed by aberration of the corresponding gene or modification of microRNA (miRNA) expression, which attenuates the gene. In a large number of cancer samples, these two mechanisms might be distributed in a coordinated and almost mutually exclusive manner. Understanding this coordination may assist in identifying changes which significantly produce the same functional impact on cancer phenotype, and further identify genes that are universally required for cancer. Present methodologies for finding aberrations usually analyze single datasets, which cannot identify such pairs of coordinating genes and miRNAs.
We have developed MIRAGAA, a statistical approach, to assess the coordinated changes of genome copy numbers and miRNA expression. We have evaluated MIRAGAA on The Cancer Genome Atlas (TCGA) Glioblastoma Multiforme datasets. In these datasets, a number of genome regions coordinating with different miRNAs are identified. Although well known for their biological significance, these genes and miRNAs would be left undetected for being less significant if the two datasets were analyzed individually.
The source code, implemented in R and java, is available from our project web site at http://www.csse.unimelb.edu.au/~rgaire/MIRAGAA/index.html.
Supplementary data are available at Bioinformatics online.
癌症通过微进化而演变，其中随机病变在多个样本中频繁发生，为癌症提供了最大优势，因此脱颖而出。同时，基因功能可以通过相应基因的异常或 miRNA（miRNA）表达的修饰而改变，从而削弱基因。在大量的癌症样本中，这两种机制可能以协调和几乎相互排斥的方式分布。了解这种协调可能有助于识别对癌症表型产生相同功能影响的显著变化，并进一步识别普遍需要癌症的基因。目前用于发现异常的方法通常分析单个数据集，无法识别这种协调的基因和 miRNA 对。
我们开发了 MIRAGAA，一种统计方法，用于评估基因组拷贝数和 miRNA 表达的协调变化。我们在 The Cancer Genome Atlas (TCGA) Glioblastoma Multiforme 数据集上评估了 MIRAGAA。在这些数据集中，确定了与不同 miRNA 协调的多个基因组区域。尽管这些基因和 miRNA 因其生物学意义而众所周知，但如果单独分析两个数据集，它们的重要性较低，可能会被遗漏。
源代码以 R 和 java 实现，可从我们的项目网站 http://www.csse.unimelb.edu.au/~rgaire/MIRAGAA/index.html 获得。
补充数据可在生物信息学在线获得。
