SURCOMED

Survival analyses based on the Kaplan-Meier estimate have been pervasively used to support or validate the relevance of biological mechanisms in cancer research. Recently, with the appearance of gene expression high-throughput technologies, this kind of analysis has been applied to tumour transcriptomics data. In a ‘bottom-up’ approach, gene-expression profiles that are associated with a deregulated pathway hypothetically involved in cancer progression are first identified and then subsequently correlated with a survival effect, which statistically supports or requires the rejection of such a hypothesis.

In this work we propose a 'top-down' approach, in which the clinical outcome (survival) is the starting point that guides the identification of deregulated biological mechanisms in cancer by a non-hypothesis-driven iterative survival analysis.

The method, named SURCOMED, was implemented as a web-based tool, which is publicly available at http://surcomed.vital-it.ch.