Biology subjects

Bjarnason, G. A.

Publications and source records attributed to Bjarnason, G. A..

3 recordsLinked to original sources

bioRxiv2026

A robust negative association between estimated tumour circadian clock function and survival in early stage breast cancer

Recent studies have established that the circadian clock influences onset, progression and therapeutic outcomes in a number of chronic conditions including cardio-metabolic diseases and cancer. For the latter, they also suggest that chronotherapy offers the potential to refine current treatments and improve the development of future anti-cancer medicines. Therefore, there is a need for tools to measure the functional state of the tumoural circadian clock in patients. We have previously developed a model-led machine-learning algorithm called TimeTeller which has the potential to provide such a tool. Here we demonstrate its potential for clinical relevance by a study of 1286 breast cancer patients in which we characterise the nature of the circadian clock disruption in their tumours and demonstrate a strong nonlinear association between 10-year survival and TimeTellers tumoural clock disfunction score {Theta}. We find that good tumour clock function is antagonistic to survival.

cancer biology↗

bioRxiv2023

TimeTeller: a tool to probe the circadian clock as a multigene dynamical system

AO_SCPLOWBSTRACTC_SCPLOWRecent studies have established that the circadian clock influences onset, progression and therapeutic outcomes in a number of diseases including cancer and heart diseases. Therefore, there is a need for tools to measure the functional state of the molecular circadian clock and its downstream targets in patients. Moreover, the clock is a multi-dimensional stochastic oscillator and there are few tools for analysing it as a system. In this paper we consider the methodology behind Time-Teller, a machine learning tool that analyses the clock as a system and aims to estimate circadian clock function from a single transcriptome by modelling the multi-dimensional state of the clock. We demonstrate its potential for clock systems assessment by applying it to mouse, baboon and human microarray and RNA-seq data and show how to visualise and quantify the global structure of the clock, quantitatively stratify individual transcriptomic samples by clock dysfunction and globally compare clocks across individuals, conditions and tissues thus highlighting its potential relevance for advancing circadian medicine.

systems biology↗

bioRxiv2019

TimeTeller: a New Tool for Precision Circadian Medicine and Cancer Prognosis

Recent studies have established that the circadian clock influences onset, progression and therapeutic outcomes in a number of diseases including cancer and heart disease. Therefore, there is a need for tools to measure the functional state of the circadian clock and its downstream targets in patients. We provide such a tool and demonstrate its clinical relevance by an application to breast cancer where we find a strong link between 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 healthy from malignant tissues and demonstrate that the molecular clock dysfunction metric is a potentially new prognostic and predictive breast cancer biomarker that is independent of the main established prognostic factors.

cancer biology↗