TimeTeller : a new tool for precision circadian medicine and cancer prognosis [preprint]

There are, however, no tools to monitor the functional state of the circadian clock and its downstream targets in humans. We provide such a tool and demonstrate its clinical relevance by an application to breast cancer where we find a strong link between overall survival and our measure of clock dysfunction.

We use a machine-learning approach and construct an algorithm called TimeTeller which uses the multi-dimensional state of the genes in a transcriptomics analysis of a single biological sample to assess the level of circadian clock dysfunction. We demonstrate how this can distinguish differences between healthy and diseased tissue and demonstrate that the clock dysfunction metric is a potentially new prognostic and predictive breast cancer biomarker that is independent of the main established prognostic factors.