Wei-Yi Cheng, Tai-Hsien Ou Yang, Hui Shen, Peter W. Laird, Dimitris Anastassiou, the Cancer Genome Atlas Research Network
Abstract
Although cancer is known to be characterized by several unifying biological hallmarks, systems biology has had limited success in identifying molecular signatures present in in all types of cancer. The current availability of rich data sets from many different cancer types provides an opportunity for thorough computational data mining in search of such common patterns. Here we report the identification of 18 "pan-cancer" molecular signatures resulting from analysis of data sets containing values from mRNA expression, microRNA expression, DNA methylation, and protein activity, from twelve different cancer types. The membership of many of these signatures points to particular biological mechanisms related to cancer progression, suggesting that they represent important attributes of cancer in need of being elucidated for potential applications in diagnostic, prognostic and therapeutic products applicable to multiple cancer types.