Brain cancer prognosis: independent validation of a clinical bioinformatics approach.
Brain cancer prognosis: independent validation of a clinical bioinformatics approach.
复制标题
DOI：
10.1186/2043-9113-2-2
复制
发表时间：
2012-02-01
期刊：
影响因子：
--
通讯作者：
Nardini, Christine
中科院分区：
文献类型：
--
作者：
Fronza, Raffaele;Tramonti, Michele;Nardini, Christine
转化医学和循证医学可以利用生物技术的进步，提供快速增长的各种高通量数据，用于筛选基因组，转录，转录后和翻译观察的分子活性。隐藏在这些数据中的临床信息可以通过临床生物信息学方法来澄清。我们最近提出了一种方法来分析不同层次的高通量（组学）数据，以保持出现在细胞系统中的所有分子水平时，相互作用的紧急属性。我们在这里表明，应用于脑癌数据的这种方法可以揭示已被独立验证为生存标志物的特性（即与不同类型脑癌中的保护性与风险特征相关的分子），在临床实践中具有潜在的重要应用。
Translational and evidence based medicine can take advantage of biotechnology advances that offer a fast growing variety of high-throughput data for screening molecular activities of genomic, transcriptional, post-transcriptional and translational observations. The clinical information hidden in these data can be clarified with clinical bioinformatics approaches. We have recently proposed a method to analyze different layers of high-throughput (omic) data to preserve the emergent properties that appear in the cellular system when all molecular levels are interacting. We show here that this method applied to brain cancer data can uncover properties (i.e. molecules related to protective versus risky features in different types of brain cancers) that have been independently validated as survival markers, with potential important application in clinical practice.