Hidalgo Marta R, Cubuk Cankut, Amadoz Alicia, Salavert Francisco, Carbonell-Caballero José, Dopazo Joaquin
Computational Genomics Department, Centro de Investigación Príncipe Felipe (CIPF), Valencia, 46012, Spain.
Functional Genomics Node (INB-ELIXIR-es), Valencia, 46012, Spain.
Oncotarget. 2017 Jan 17;8(3):5160-5178. doi: 10.18632/oncotarget.14107.
Understanding the aspects of the cell functionality that account for disease or drug action mechanisms is a main challenge for precision medicine. Here we propose a new method that models cell signaling using biological knowledge on signal transduction. The method recodes individual gene expression values (and/or gene mutations) into accurate measurements of changes in the activity of signaling circuits, which ultimately constitute high-throughput estimations of cell functionalities caused by gene activity within the pathway. Moreover, such estimations can be obtained either at cohort-level, in case/control comparisons, or personalized for individual patients. The accuracy of the method is demonstrated in an extensive analysis involving 5640 patients from 12 different cancer types. Circuit activity measurements not only have a high diagnostic value but also can be related to relevant disease outcomes such as survival, and can be used to assess therapeutic interventions.
理解导致疾病或药物作用机制的细胞功能方面是精准医学面临的主要挑战。在此，我们提出一种新方法，该方法利用信号转导的生物学知识对细胞信号传导进行建模。该方法将个体基因表达值（和/或基因突变）重新编码为信号传导回路活性变化的精确测量值，这些测量值最终构成了对通路内基因活性引起的细胞功能的高通量估计。此外，这种估计既可以在队列水平上进行，用于病例/对照比较，也可以针对个体患者进行个性化分析。该方法的准确性在一项涉及来自12种不同癌症类型的5640名患者的广泛分析中得到了证明。信号传导回路活性测量不仅具有很高的诊断价值，而且还可以与生存等相关疾病结局相关联，并可用于评估治疗干预措施。
