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Giacchetti, S.

Publications and source records attributed to Giacchetti, S..

2 recordsLinked to original sources

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↗

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↗